Influence of Mass Resolving Power in Orbital Ion-Trap Mass Spectrometry-Based Metabolomics.
Modern separation methods in conjunction with high-resolution accurate mass (HRAM) spectrometry can provide an enormous number of features characterized by exact mass and chromatographic behavior. Higher mass resolving power usually requires longer scanning times, and thus fewer data points are acquired across the target peak. This could cause difficulties for quantification, feature detection and deconvolution. The aim of this work was to describe the influence of mass spectrometry resolving power on profiling metabolomics experiments. From metabolic databases (HMDB, LipidMaps, KEGG), a list of compounds (41 474) was compiled and potential adducts and isotopes were calculated (622 110 features). The number of distinguishable masses was calculated for up to 3840k resolution. To evaluate these models, human plasma samples were analyzed by LC-HRMS on an Orbitrap Elite hybrid mass spectrometer (Thermo Fisher Scientific, CA, USA) at resolving power settings of 15k (7.8 Hz) up to a maximum of 480k (1.2 Hz). Software XCMS 1.44, MZmine 2.13.1, and Compound Discoverer 2.0.0.303 were used for evaluation. In plasma samples, the number of detected features increased sharply up to 60k in both positive and negative mode. However, beyond these values, it either flattened out or decreased owing to technical limitations. In conclusion, the most effective mass resolving powers for profiling analyses of metabolite rich biofluids on the Orbitrap Elite were around 60 000-120 000 fwhm to retrieve the highest amount of information. The region between 400-800 m/z was influenced the most by resolution.
Laboratory of Metabolomics, Institute of Molecular and Translational Medicine, Palacký University in Olomouc , Hněvotínská 5, 775 15 Olomouc, Czech Republic.|University Hospital Olomouc , I.P. Pavlova 185/6, 779 00 Olomouc, Czech Republic.
Lukáš
L
Najdekr
Laboratory of Metabolomics, Institute of Molecular and Translational Medicine, Palacký University in Olomouc , Hněvotínská 5, 775 15 Olomouc, Czech Republic.|University Hospital Olomouc , I.P. Pavlova 185/6, 779 00 Olomouc, Czech Republic.
David
D
Friedecký
Thermo Fisher Scientific , 355 River Oaks Parkway, San Jose, 95134 California United States.
Ralf
R
Tautenhahn
Whitehead Institute for Biomedical Research , 9 Cambridge Center, Cambridge, Massachusetts 02142-1479, United States.
Tomáš
T
Pluskal
Thermo Fisher Scientific , 355 River Oaks Parkway, San Jose, 95134 California United States.
Junhua
J
Wang
Thermo Fisher Scientific , 355 River Oaks Parkway, San Jose, 95134 California United States.
Yingying
Y
Huang
Laboratory of Metabolomics, Institute of Molecular and Translational Medicine, Palacký University in Olomouc , Hněvotínská 5, 775 15 Olomouc, Czech Republic.|University Hospital Olomouc , I.P. Pavlova 185/6, 779 00 Olomouc, Czech Republic.
Tomáš
T
Adam
D002853:Chromatography, Liquid; D003198:Computer Simulation; D016208:Databases, Factual; D064368:Healthy Volunteers; D006801:Humans; D008055:Lipids / Q000097:blood*; D013058:Mass Spectrometry; D055432:Metabolomics; D015394:Molecular Structure
D008055:Lipids