scholarly journals TIMSCONVERT: A workflow to convert trapped ion mobility data to open data formats

2021 ◽  
Author(s):  
Gordon T Luu ◽  
Itzel Lizama-Chamu ◽  
Catherine S McCaughey ◽  
Laura M Sanchez ◽  
Mingxun Wang
Keyword(s):  
Data Analysis ◽  
Ion Mobility ◽  
Open Data ◽  
Data Conversion ◽  
Mass Spectrometers ◽  
Mobility Separation ◽  
Mobility Data ◽  
Data Files ◽  
Using Data ◽  
Ion Mobility Separation

Advances in mass spectrometry instrumentation have led to the development of mass spectrometers with ion mobility separation (IMS) capabilities and dual source instrumentation, but the current software ecosystem lacks interoperability with downstream data analysis using open-source software/pipelines. Here, we present TIMSCONVERT, a data conversion workflow from timsTOF fleX MS raw data files to size conscious mzML and imzML formats with minimal preprocessing to allow for compatibility with downstream data analysis tools, which we showcase with several examples using data acquired across different experiments and acquisition modalities on the timsTOF fleX. Availability and Implementation: TIMSCONVERT and its documentation can be found at https://github.com/gtluu/timsconvert and is available as a standalone command line interface, Nextflow workflow, and online in the Global Natural Products Social (GNPS) platform (https://proteomics2.ucsd.edu/ProteoSAFe/index.jsp?params={%22workflow%22%3A%20%22T IMSCONVERT%22}).

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>

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 High sensitivity dia-PASEF proteomics with DIA-NN and FragPipe

2021 ◽  
Author(s):  
Vadim Demichev ◽  
Fengchao Yu ◽  
Guo Ci Teo ◽  
Lukasz Szyrwiel ◽  
George A. Rosenberger ◽  
...  
Keyword(s):  
Neural Network ◽  
Ion Mobility ◽  
High Sensitivity ◽  
Software Suite ◽  
Complex Samples ◽  
Mobility Separation ◽  
Mobility Data ◽  
Ion Mobility Separation ◽  
Spectral Libraries ◽  
Computational Platform

AbstractThe dia-PASEF technology exploits ion mobility separation for high-sensitivity analysis of complex proteomes. Here, we demonstrate neural network-based processing of the ion mobility data, which we implement in the DIA-NN software suite. Using spectral libraries generated with the MSFragger-based FragPipe computational platform, the DIA-NN analysis of dia-PASEF raw data increases the proteomic depth by up to 69% compared to the originally published dia-PASEF workflow. For example, we quantify over 5200 proteins from 10ng of HeLa peptides separated with a 95-minute nanoflow gradient, and over 5000 proteins from 200ng using a 4.8-minute separation with an Evosep One system. In complex samples, featuring a mix of human and yeast lysates, the workflow detects over 11700 proteins in single runs acquired with a 100-minute nanoflow gradient, while demonstrating quantitative precision. Hence, the combination of FragPipe and DIA-NN provides a simple-to-use software platform for dia-PASEF data analysis, yielding significant gains in high-sensitivity proteomics.

Proteomic Profile of Daphnia pulex using Data-Independent Acquisition Mass Spectrometry and Ion Mobility Separation

PROTEOMICS ◽  
2018 ◽  
Vol 18 (16) ◽  
pp. 1700460 ◽  
Author(s):  
Aaron Steevensz ◽  
Robert Gombar ◽  
Roland Vergilino ◽  
Melania E. Cristescu ◽  
Panayiotis O. Vacratsis
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Daphnia Pulex ◽  
Proteomic Profile ◽  
Mobility Separation ◽  
Data Independent Acquisition ◽  
Using Data ◽  
Ion Mobility Separation

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.

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