Nearline acquisition and processing of liquid chromatography-tandem mass spectrometry data

Neumann, Steffen; Thum, Andrea; Böttcher, Christoph

doi:10.1007/s11306-012-0401-0

Cited by 29 publications

(26 citation statements)

References 23 publications

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“…As this paper used existing benchmark data from spectral libraries, we have described a metabolomics workflow elsewhere . The MetShot approach first obtains a list of peaks of interest from metabolite profiling and statistical analysis and acquires high‐quality tandem mass spectra, which can be converted to MetFusion batch query files.…”

Section: Discussionmentioning

confidence: 99%

MetFusion: integration of compound identification strategies

2013

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Mass spectrometry (MS) is an important analytical technique for the detection and identification of small compounds. The main bottleneck in the interpretation of metabolite profiling or screening experiments is the identification of unknown compounds from tandem mass spectra. Spectral libraries for tandem MS, such as MassBank or NIST, contain reference spectra for many compounds, but their limited chemical coverage reduces the chance for a correct and reliable identification of unknown spectra outside the database domain. On the other hand, compound databases like PubChem or ChemSpider have a much larger coverage of the chemical space, but they cannot be queried with spectral information directly. Recently, computational mass spectrometry methods and in silico fragmentation prediction allow users to search such databases of chemical structures. We present a new strategy called MetFusion to combine identification results from several resources, in particular, from the in silico fragmenter MetFrag with the spectral library MassBank to improve compound identification. We evaluate the performance on a set of 1062 spectra and achieve an improved ranking of the correct compound from rank 28 using MetFrag alone, to rank 7 with MetFusion, even if the correct compound and similar compounds are absent from the spectral library. On the basis of the evaluation, we extrapolate the performance of MetFusion to the KEGG compound database.

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Section: Discussionmentioning

confidence: 99%

MetFusion: integration of compound identification strategies

2013

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“…As a consequence, some biologically relevant precursor ions may not be selected for fragmentation if they do not match the defined selection criteria or if they are coeluted with more intense species. These issues can be partially overcome by the use and careful optimization of additional MS-to-MS/MS triggering criteria (e.g., isotope pattern or mass defect) [8][9][10], by optimizing the use of exclusion or inclusion lists prior to further MS/MS acquisitions [11][12][13], or by implementing efficient software tools for assessing precursor ion purity of acquired data [14].Until very recently, the implementation of acquisition protocols combining MS and MS/MS acquisitions in one single run, especially those related to DIA, were rather limited to hybrid quadrupole-time-of-flight (Q-TOF) instruments due to their enhanced duty cycles [15,16]. Because of their lower acquisition speed, simultaneous MS and MS/MS data collection can rarely be performed at the highest mass resolution achievable on Orbitrap-based instruments, in order to keep enough data points per chromatographic peak, which is mandatory for further reliable peak integration and corresponding metabolite quantification from MS data [17].…”

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confidence: 99%

Comparative Evaluation of Data Dependent and Data Independent Acquisition Workflows Implemented on an Orbitrap Fusion for Untargeted Metabolomics

et al. 2020

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Constant improvements to the Orbitrap mass analyzer, such as acquisition speed, resolution, dynamic range and sensitivity have strengthened its value for the large-scale identification and quantification of metabolites in complex biological matrices. Here, we report the development and optimization of Data Dependent Acquisition (DDA) and Sequential Window Acquisition of all THeoretical fragment ions (SWATH-type) Data Independent Acquisition (DIA) workflows on a high-field Orbitrap FusionTM TribridTM instrument for the robust identification and quantification of metabolites in human plasma. By using a set of 47 exogenous and 72 endogenous molecules, we compared the efficiency and complementarity of both approaches. We exploited the versatility of this mass spectrometer to collect meaningful MS/MS spectra at both high- and low-mass resolution and various low-energy collision-induced dissociation conditions under optimized DDA conditions. We also observed that complex and composite DIA-MS/MS spectra can be efficiently exploited to identify metabolites in plasma thanks to a reference tandem spectral library made from authentic standards while also providing a valuable data resource for further identification of unknown metabolites. Finally, we found that adding multi-event MS/MS acquisition did not degrade the ability to use survey MS scans from DDA and DIA workflows for the reliable absolute quantification of metabolites down to 0.05 ng/mL in human plasma.

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“…Rather, MS 2 is triggered based on the previously acquired and processed files that have already been uploaded and analyzed by XCMS Online. The data processing involved with automated selection of ions targeted for MS 2 analysis is analogous to that which has already been described 7 , but here ion selection and MS 2 acquisition will occur within the same set of experimental runs. In this context, XCMS-based streaming allows for biological-dependent data acquisition.…”

Section: To the Editormentioning

confidence: 99%