Comparison of Three Untargeted Data Processing Workflows for Evaluating LC-HRMS Metabolomics Data

Abstract

The evaluation of liquid chromatography high-resolution mass spectrometry (LC-HRMS) raw data is a crucial step in untargeted metabolomics studies to minimize false positive findings. A variety of commercial or open source software solutions are available for such data processing. This study aims to compare three different data processing workflows (Compound Discoverer 3.1, XCMS Online combined with MetaboAnalyst 4.0, and a manually programmed tool using R) to investigate LC-HRMS data of an untargeted metabolomics study. Simple but highly standardized datasets for evaluation were prepared by incubating pHLM (pooled human liver microsomes) with the synthetic cannabinoid A-CHMINACA. LC-HRMS analysis was performed using normal- and reversed-phase chromatography followed by full scan MS in positive and negative mode. MS/MS spectra of significant features were subsequently recorded in a separate run. The outcome of each workflow was evaluated by its number of significant features, peak shape quality, and the results of the multivariate statistics. Compound Discoverer as an all-in-one solution is characterized by its ease of use and seems, therefore, suitable for simple and small metabolomic studies. The two open source solutions allowed extensive customization but particularly, in the case of R, made advanced programming skills necessary. Nevertheless, both provided high flexibility and may be suitable for more complex studies and questions.

Untargeted Metabolomics Analysis Using FTIR and UHPLC-Q-Orbitrap HRMS of Two Curculigo Species and Evaluation of Their Antioxidant and α-Glucosidase Inhibitory Activities

“…( ) using peak areas data (*.csv format) from all compounds detected in the adduct type ([M + H] + and [M − H] − ) of each organ of Curculigo species. For hierarchical clustering analysis, distance measures using Euclidean, clustering algorithms using complete, and standardization using autoscale were chosen [ 30 , 47 ].…”

Phase I In Vitro Metabolic Profiling of the Synthetic Cannabinoid Receptor Agonists CUMYL-THPINACA and ADAMANTYL-THPINACA

“…ADAMANTYL-THPINACA was prone to hydroxylation at the adamantyl-moiety and, to a lesser extent, at the 1-(tetrahydropyranyl-4-methyl)-indazole-3-carboxamide-moiety. Extensive hydroxylation at the adamantyl-moiety has also been observed for other adamantyl-bearing SCRAs [ 31 , 46 , 47 ]. Overall, one mono-hydroxylated (M12), three di-hydroxylated (MA5, MA7, MA9), and four tri-hydroxylated (MA1, MA2, MA4, MA6) were detected.…”

Metabolomic Studies for the Evaluation of Toxicity Induced by Environmental Toxicants on Model Organisms

“…Additionally, a comprehensive analysis of metabolite extracts can be achieved via data-dependent analysis (DDA) or data-independent analysis (DIA), which can yield hundreds to thousands of peaks [ 98 , 99 ]. Thus, the identification process can be easily processed using highly advanced data processing techniques and by comparing established online or in-house libraries [ 100 , 101 ]. Furthermore, with the advances in analysis and data processing techniques, it is now possible to obtain much higher quality data than those obtained in the past.…”