On-tissue dataset-dependent MALDI-TIMS-MS2 bioimaging

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388963%3A_____%2F23%3A00578317" target="_blank" >RIV/61388963:_____/23:00578317 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1038/s41467-023-43298-9" target="_blank" >https://doi.org/10.1038/s41467-023-43298-9</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41467-023-43298-9" target="_blank" >10.1038/s41467-023-43298-9</a>

Jazyk výsledku

angličtina

Název v původním jazyce

On-tissue dataset-dependent MALDI-TIMS-MS2 bioimaging

Popis výsledku v původním jazyce

Trapped ion mobility spectrometry (TIMS) adds an additional separation dimension to mass spectrometry (MS) imaging, however, the lack of fragmentation spectra (MS2) impedes confident compound annotation in spatial metabolomics. Here, we describe spatial ion mobility-scheduled exhaustive fragmentation (SIMSEF), a dataset-dependent acquisition strategy that augments TIMS-MS imaging datasets with MS2 spectra. The fragmentation experiments are systematically distributed across the sample and scheduled for multiple collision energies per precursor ion. Extendable data processing and evaluation workflows are implemented into the open source software MZmine. The workflow and annotation capabilities are demonstrated on rat brain tissue thin sections, measured by matrix-assisted laser desorption/ionisation (MALDI)-TIMS-MS, where SIMSEF enables on-tissue compound annotation through spectral library matching and rule-based lipid annotation within MZmine and maps the (un)known chemical space by molecular networking. The SIMSEF algorithm and data analysis pipelines are open source and modular to provide a community resource.

Název v anglickém jazyce

On-tissue dataset-dependent MALDI-TIMS-MS2 bioimaging

Popis výsledku anglicky

Trapped ion mobility spectrometry (TIMS) adds an additional separation dimension to mass spectrometry (MS) imaging, however, the lack of fragmentation spectra (MS2) impedes confident compound annotation in spatial metabolomics. Here, we describe spatial ion mobility-scheduled exhaustive fragmentation (SIMSEF), a dataset-dependent acquisition strategy that augments TIMS-MS imaging datasets with MS2 spectra. The fragmentation experiments are systematically distributed across the sample and scheduled for multiple collision energies per precursor ion. Extendable data processing and evaluation workflows are implemented into the open source software MZmine. The workflow and annotation capabilities are demonstrated on rat brain tissue thin sections, measured by matrix-assisted laser desorption/ionisation (MALDI)-TIMS-MS, where SIMSEF enables on-tissue compound annotation through spectral library matching and rule-based lipid annotation within MZmine and maps the (un)known chemical space by molecular networking. The SIMSEF algorithm and data analysis pipelines are open source and modular to provide a community resource.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10608 - Biochemistry and molecular biology

Projekt

<a href="/cs/project/GM21-11563M" target="_blank" >GM21-11563M: Mapování chemodiverzity pepřovníkovitých rostlin pomocí nové generace platformy MZmine</a><br>

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Nature Communications

ISSN

2041-1723

e-ISSN

2041-1723

Svazek periodika

14

Číslo periodika v rámci svazku

November

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

9

Strana od-do

7495

Kód UT WoS článku

001106858800048

EID výsledku v databázi Scopus

2-s2.0-85176926137