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  1. Article ; Online: Chemical Discovery in the Era of Metabolomics.

    Sindelar, Miriam / Patti, Gary J

    Journal of the American Chemical Society

    2020  Volume 142, Issue 20, Page(s) 9097–9105

    Abstract: Untargeted metabolomics aims to quantify the complete set of metabolites within a biological system, most commonly by liquid chromatography/mass spectrometry (LC/MS). Since nearly the inception of the field, compound identification has been widely ... ...

    Abstract Untargeted metabolomics aims to quantify the complete set of metabolites within a biological system, most commonly by liquid chromatography/mass spectrometry (LC/MS). Since nearly the inception of the field, compound identification has been widely recognized as the rate-limiting step of the experimental workflow. In spite of exponential increases in the size of metabolomic databases, which now contain experimental MS/MS spectra for over a half a million reference compounds, chemical structures still cannot be confidently assigned to many signals in a typical LC/MS dataset. The purpose of this Perspective is to consider why identification rates continue to be low in untargeted metabolomics. One rationalization is that many naturally occurring metabolites detected by LC/MS are true "novel" compounds that have yet to be incorporated into metabolomic databases. An alternative possibility, however, is that research data do not provide database matches because of informatic artifacts, chemical contaminants, and signal redundancies. Increasing evidence suggests that, for at least some sample types, many unidentifiable signals in untargeted metabolomics result from the latter rather than new compounds originating from the specimen being measured. The implications of these observations on chemical discovery in untargeted metabolomics are discussed.
    MeSH term(s) Animals ; Chromatography, Liquid ; Escherichia coli/metabolism ; Humans ; Mass Spectrometry ; Metabolomics
    Language English
    Publishing date 2020-05-11
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Review
    ZDB-ID 3155-0
    ISSN 1520-5126 ; 0002-7863
    ISSN (online) 1520-5126
    ISSN 0002-7863
    DOI 10.1021/jacs.9b13198
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Chemical Discovery in the Era of Metabolomics

    Sindelar, Miriam / Patti, Gary J

    Journal of the American Chemical Society. 2020 Apr. 10, v. 142, no. 20

    2020  

    Abstract: Untargeted metabolomics aims to quantify the complete set of metabolites within a biological system, most commonly by liquid chromatography/mass spectrometry (LC/MS). Since nearly the inception of the field, compound identification has been widely ... ...

    Abstract Untargeted metabolomics aims to quantify the complete set of metabolites within a biological system, most commonly by liquid chromatography/mass spectrometry (LC/MS). Since nearly the inception of the field, compound identification has been widely recognized as the rate-limiting step of the experimental workflow. In spite of exponential increases in the size of metabolomic databases, which now contain experimental MS/MS spectra for over a half a million reference compounds, chemical structures still cannot be confidently assigned to many signals in a typical LC/MS dataset. The purpose of this Perspective is to consider why identification rates continue to be low in untargeted metabolomics. One rationalization is that many naturally occurring metabolites detected by LC/MS are true “novel” compounds that have yet to be incorporated into metabolomic databases. An alternative possibility, however, is that research data do not provide database matches because of informatic artifacts, chemical contaminants, and signal redundancies. Increasing evidence suggests that, for at least some sample types, many unidentifiable signals in untargeted metabolomics result from the latter rather than new compounds originating from the specimen being measured. The implications of these observations on chemical discovery in untargeted metabolomics are discussed.
    Keywords chemical pollutants ; chemical structure ; data collection ; databases ; liquid chromatography ; metabolites ; metabolomics ; tandem mass spectrometry
    Language English
    Dates of publication 2020-0410
    Size p. 9097-9105.
    Publishing place American Chemical Society
    Document type Article
    ZDB-ID 3155-0
    ISSN 1520-5126 ; 0002-7863
    ISSN (online) 1520-5126
    ISSN 0002-7863
    DOI 10.1021/jacs.9b13198
    Database NAL-Catalogue (AGRICOLA)

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  3. Article ; Online: An Untargeted Metabolomics Workflow that Scales to Thousands of Samples for Population-Based Studies.

    Stancliffe, Ethan / Schwaiger-Haber, Michaela / Sindelar, Miriam / Murphy, Matthew J / Soerensen, Mette / Patti, Gary J

    Analytical chemistry

    2022  Volume 94, Issue 50, Page(s) 17370–17378

    Abstract: The success of precision medicine relies upon collecting data from many individuals at the population level. Although advancing technologies have made such large-scale studies increasingly feasible in some disciplines such as genomics, the standard ... ...

    Abstract The success of precision medicine relies upon collecting data from many individuals at the population level. Although advancing technologies have made such large-scale studies increasingly feasible in some disciplines such as genomics, the standard workflows currently implemented in untargeted metabolomics were developed for small sample numbers and are limited by the processing of liquid chromatography/mass spectrometry data. Here we present an untargeted metabolomics workflow that is designed to support large-scale projects with thousands of biospecimens. Our strategy is to first evaluate a reference sample created by pooling aliquots of biospecimens from the cohort. The reference sample captures the chemical complexity of the biological matrix in a small number of analytical runs, which can subsequently be processed with conventional software such as XCMS. Although this generates thousands of so-called features, most do not correspond to unique compounds from the samples and can be filtered with established informatics tools. The features remaining represent a comprehensive set of biologically relevant reference chemicals that can then be extracted from the entire cohort's raw data on the basis of
    MeSH term(s) Humans ; Workflow ; Metabolomics/methods ; Mass Spectrometry/methods ; Chromatography, Liquid/methods ; Software
    Language English
    Publishing date 2022-12-07
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 1508-8
    ISSN 1520-6882 ; 0003-2700
    ISSN (online) 1520-6882
    ISSN 0003-2700
    DOI 10.1021/acs.analchem.2c01270
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: DecoID improves identification rates in metabolomics through database-assisted MS/MS deconvolution.

    Stancliffe, Ethan / Schwaiger-Haber, Michaela / Sindelar, Miriam / Patti, Gary J

    Nature methods

    2021  Volume 18, Issue 7, Page(s) 779–787

    Abstract: Chimeric MS/MS spectra contain fragments from multiple precursor ions and therefore hinder compound identification in metabolomics. Historically, deconvolution of these chimeric spectra has been challenging and relied on specific experimental methods ... ...

    Abstract Chimeric MS/MS spectra contain fragments from multiple precursor ions and therefore hinder compound identification in metabolomics. Historically, deconvolution of these chimeric spectra has been challenging and relied on specific experimental methods that introduce variation in the ratios of precursor ions between multiple tandem mass spectrometry (MS/MS) scans. DecoID provides a complementary, method-independent approach where database spectra are computationally mixed to match an experimentally acquired spectrum by using LASSO regression. We validated that DecoID increases the number of identified metabolites in MS/MS datasets from both data-independent and data-dependent acquisition without increasing the false discovery rate. We applied DecoID to publicly available data from the MetaboLights repository and to data from human plasma, where DecoID increased the number of identified metabolites from data-dependent acquisition data by over 30% compared to direct spectral matching. DecoID is compatible with any user-defined MS/MS database and provides automated searching for some of the largest MS/MS databases currently available.
    MeSH term(s) Algorithms ; Blood/metabolism ; Databases, Factual ; Escherichia coli/metabolism ; Humans ; Metabolomics/methods ; Reproducibility of Results ; Saccharomycetales/metabolism ; Signal Processing, Computer-Assisted ; Tandem Mass Spectrometry/methods
    Language English
    Publishing date 2021-07-08
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 2169522-2
    ISSN 1548-7105 ; 1548-7091
    ISSN (online) 1548-7105
    ISSN 1548-7091
    DOI 10.1038/s41592-021-01195-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  5. Book ; Thesis: Entwicklung einer Methode zum Screening pseudostatischer Substanzbibliotheken mittels MS-Bindungsassays für das Target mGAT1

    Sindelar, Miriam

    (Pharmazeutische Chemie)

    2013  

    Author's details Miriam Sindelar
    Series title Pharmazeutische Chemie
    Language German
    Size VII, 417 S., 210 mm x 148 mm, 649 g
    Publisher Dr. Hut
    Publishing place München
    Document type Book ; Thesis
    Thesis / German Habilitation thesis Ludwig-Maximilians-Univ., Diss.--München, 2013
    ISBN 3843912866 ; 9783843912860
    Database Former special subject collection: coastal and deep sea fishing

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  6. Article ; Online: Quantitative rotational-echo double resonance for Carbon-13 spin clusters.

    Matsuoka, Shigeru / Sindelar, Miriam / Bansal, Sonal / Patti, Gary J / Schaefer, Jacob

    Journal of magnetic resonance (San Diego, Calif. : 1997)

    2021  Volume 330, Page(s) 107043

    Abstract: By using only half of the total evolution time for dephasing pulses, C{N} rotational-echo double resonance (REDOR) for clusters ... ...

    Abstract By using only half of the total evolution time for dephasing pulses, C{N} rotational-echo double resonance (REDOR) for clusters of
    MeSH term(s) Carbon Isotopes ; Humans ; Magnetic Resonance Spectroscopy ; Nitrogen Isotopes
    Chemical Substances Carbon Isotopes ; Nitrogen Isotopes ; Carbon-13 (FDJ0A8596D)
    Language English
    Publishing date 2021-07-22
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural
    ZDB-ID 1469665-4
    ISSN 1096-0856 ; 1557-8968 ; 1090-7807 ; 0022-2364
    ISSN (online) 1096-0856 ; 1557-8968
    ISSN 1090-7807 ; 0022-2364
    DOI 10.1016/j.jmr.2021.107043
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: A Workflow to Perform Targeted Metabolomics at the Untargeted Scale on a Triple Quadrupole Mass Spectrometer

    Michaela Schwaiger-Haber / Ethan Stancliffe / Valerie Arends / Bharat Thyagarajan / Miriam Sindelar / Gary J. Patti

    ACS Measurement Science Au, Vol 1, Iss 1, Pp 35-

    2021  Volume 45

    Keywords Analytical chemistry ; QD71-142
    Language English
    Publishing date 2021-07-01T00:00:00Z
    Publisher American Chemical Society
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: A Workflow to Perform Targeted Metabolomics at the Untargeted Scale on a Triple Quadrupole Mass Spectrometer.

    Schwaiger-Haber, Michaela / Stancliffe, Ethan / Arends, Valerie / Thyagarajan, Bharat / Sindelar, Miriam / Patti, Gary J

    ACS measurement science au

    2021  Volume 1, Issue 1, Page(s) 35–45

    Abstract: The thousands of features commonly observed when performing untargeted metabolomics with quadrupole time-of-flight (QTOF) and Orbitrap mass spectrometers often correspond to only a few hundred unique metabolites of biological origin, which is in the ... ...

    Abstract The thousands of features commonly observed when performing untargeted metabolomics with quadrupole time-of-flight (QTOF) and Orbitrap mass spectrometers often correspond to only a few hundred unique metabolites of biological origin, which is in the range of what can be assayed in a single targeted metabolomics experiment by using a triple quadrupole (QqQ) mass spectrometer. A major benefit of performing targeted metabolomics with QqQ mass spectrometry is the affordability of the instruments relative to high-resolution QTOF and Orbitrap platforms. Optimizing targeted methods to profile hundreds of metabolites on a QqQ mass spectrometer, however, has historically been limited by the availability of authentic standards, particularly for "unknowns" that have yet to be structurally identified. Here, we report a strategy to develop multiple reaction monitoring (MRM) methods for QqQ instruments on the basis of high-resolution spectra, thereby enabling us to use data from untargeted metabolomics to design targeted experiments without the need for authentic standards. We demonstrate that using high-resolution fragmentation data alone to design MRM methods results in the same quantitative performance as when methods are optimized by measuring authentic standards on QqQ instruments, as is conventionally done. The approach was validated by showing that Orbitrap ID-X data can be used to establish MRM methods on a Thermo TSQ Altis and two Agilent QqQs for hundreds of metabolites, including unknowns, without a dependence on standards. Finally, we highlight an application where metabolite profiling was performed on an ID-X and a QqQ by using the strategy introduced here, with both data sets yielding the same result. The described approach therefore allows us to use QqQ instruments, which are often associated with targeted metabolomics, to profile knowns and unknowns at a comprehensive scale that is typical of untargeted metabolomics.
    Language English
    Publishing date 2021-07-22
    Publishing country United States
    Document type Journal Article
    ISSN 2694-250X
    ISSN (online) 2694-250X
    DOI 10.1021/acsmeasuresciau.1c00007
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Targeting unique biological signals on the fly to improve MS/MS coverage and identification efficiency in metabolomics.

    Cho, Kevin / Schwaiger-Haber, Michaela / Naser, Fuad J / Stancliffe, Ethan / Sindelar, Miriam / Patti, Gary J

    Analytica chimica acta

    2021  Volume 1149, Page(s) 338210

    Abstract: When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is common to detect thousands of features from a biological extract. Although it is impractical to collect non-chimeric MS/MS data for each in a single ... ...

    Abstract When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is common to detect thousands of features from a biological extract. Although it is impractical to collect non-chimeric MS/MS data for each in a single chromatographic run, this is generally unnecessary because most features do not correspond to unique metabolites of biological relevance. Here we show that relatively simple data-processing strategies that can be applied on the fly during acquisition of data with an Orbitrap ID-X, such as blank subtraction and well-established adduct or isotope calculations, decrease the number of features to target for MS/MS analysis by up to an order of magnitude for various types of biological matrices. We demonstrate that annotating these non-biological contaminants and redundancies in real time during data acquisition enables comprehensive MS/MS data to be acquired on each remaining feature at a single collision energy. To ensure that an appropriate collision energy is applied, we introduce a method using a series of hidden ion-trap scans in an Orbitrap ID-X to find an optimal value for each feature that can then be applied in a subsequent high-resolution Orbitrap scan. Data from 100 metabolite standards indicate that this real-time optimization of collision energies leads to more informative MS/MS patterns compared to using a single fixed collision energy alone. As a benchmark to evaluate the overall workflow, we manually annotated unique biological features by independently subjecting E. coli samples to a credentialing analysis. While credentialing led to a more rigorous reduction in feature number, on-the-fly annotation with blank subtraction on an Orbitrap ID-X did not inappropriately discard unique biological metabolites. Taken together, our results reveal that optimal fragmentation data can be obtained in a single LC/MS/MS run for >90% of the unique biological metabolites in a sample when features are annotated during acquisition and collision energies are selected by using parallel mass spectrometry detection.
    MeSH term(s) Chromatography, Liquid ; Escherichia coli ; Metabolomics ; Tandem Mass Spectrometry ; Workflow
    Language English
    Publishing date 2021-01-12
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 1483436-4
    ISSN 1873-4324 ; 0003-2670
    ISSN (online) 1873-4324
    ISSN 0003-2670
    DOI 10.1016/j.aca.2021.338210
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Book ; Online ; Thesis: Entwicklung einer Methode zum Screening pseudostatischer Substanzbibliotheken mittels MS-Bindungsassays für das Target mGAT1

    Sindelar, Miriam [Verfasser]

    2013  

    Author's details Miriam Sindelar
    Keywords Medizin, Gesundheit ; Medicine, Health
    Subject code sg610
    Language German
    Publisher Verlag Dr. Hut
    Publishing place München
    Document type Book ; Online ; Thesis
    ISBN 978-3-8439-1286-0 ; 3-8439-1286-6
    Database Digital theses on the web

    Full text online

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