Data-Independent Acquisition for the Quantification and Identification of Metabolites in Plasma

Abstract

A popular fragmentation technique for non-targeted analysis is called data-independent acquisition (DIA), because it provides fragmentation data for all analytes in a specific mass range. In this work, we demonstrated the strengths and weaknesses of DIA. Two types of chromatography (fractionation/3 min and hydrophilic interaction liquid chromatography (HILIC)/18 min) and three DIA protocols (variable sequential window acquisition of all theoretical mass spectra (SWATH), fixed SWATH and MSALL) were used to evaluate the performance of DIA. Our results show that fast chromatography and MSALL often results in product ion overlap and complex MS/MS spectra, which reduces the quantitative and qualitative power of these DIA protocols. The combination of SWATH and HILIC allowed for the correct identification of 20 metabolites using the NIST library. After SWATH window customization (i.e., variable SWATH), we were able to quantify ten structural isomers with a mean accuracy of 103% (91–113%). The robustness of the variable SWATH and HILIC method was demonstrated by the accurate quantification of these structural isomers in 10 highly diverse blood samples. Since the combination of variable SWATH and HILIC results in good quantitative and qualitative fragmentation data, it is promising for both targeted and untargeted platforms. This should decrease the number of platforms needed in metabolomics and increase the value of a single analysis.

Impact of the Glycemic Level on the Salivary Proteome of Middle-Aged and Elderly People With Type 2 Diabetes Mellitus: An Observational Study

“…During the DIA process, it is independent of the composition of precursor ions for their fragmentation to implement the approach, and thus, this method improves the accuracy and precision of quantitation and has gained much popularity (Zhang et al, 2020a). This technique is widely used in various body fluids, including blood, cerebrospinal fluid, urine, and tears but is less applied in saliva (Li et al, 2020;van der Laan et al, 2020;Cheung et al, 2021;Jia et al, 2021).…”

Analyzing Assay Specificity in Metabolomics Using Unique Ion Signature Simulations

“…This work uses simulations to showcase DIA as an emerging MS acquisition method with high selectivity for metabolomics, consistent with previous experimental work in the field. 5,8,20,25,26 Here we quantitatively show the impact that orthogonal information contributed from both MS1 and MS2 levels has on compound detection and differentiation from background compounds using m/z separation. Additionally, these findings support the need for an efficient pipeline for DIA analysis, building upon current tools in the field (i.e., MetaboDIA, MetDIA, MS-DIAL).…”

Novel Strategy for Untargeted Chiral Metabolomics using Liquid Chromatography-High Resolution Tandem Mass Spectrometry

“…For untargeted metabolomic analysis of complex biological matrices, the AIF scan has been a commonly used DIA strategy in recent years. , Since AIF scan can acquire MS/MS spectra for all precursor ions in a specific mass range simultaneously without any prior knowledge about precursor, thereby maximizes metabolic features and MS/MS spectral coverage . On the contrary, the more selective targeted approaches such as parallel reaction monitoring (PRM) require a predefined inclusion list of precursor ions and only acquire MS/MS spectra of preselected features. − Moreover, a relatively slow scan speed of PRM allows monitoring of a few targets during a certain time interval, therefore it is preferred for targeted metabolomic analysis. , …”