Non-targeted analysis of unexpected food contaminants using LC-HRMS

Abstract

A non-target analysis method for unexpected contaminants in food is described. Many current methods referred to as “non-target” are capable of detecting hundreds or even thousands of contaminants. However, they will typically still miss all other possible contaminants. Instead, a metabolomics approach might be used to obtain “true non-target” analysis. In the present work, such a method was optimized for improved detection capability at low concentrations. The method was evaluated using 19 chemically diverse model compounds spiked into milk samples to mimic unknown contamination. Other milk samples were used as reference samples. All samples were analyzed with UHPLC-TOF-MS (ultra-high-performance liquid chromatography time-of-flight mass spectrometry), using reversed-phase chromatography and electrospray ionization in positive mode. Data evaluation was performed by the software TracMass 2. No target lists of specific compounds were used to search for the contaminants. Instead, the software was used to sort out all features only occurring in the spiked sample data, i.e., the workflow resembled a metabolomics approach. Procedures for chemical identification of peaks were outside the scope of the study. Method, study design, and settings in the software were optimized to minimize manual evaluation and faulty or irrelevant hits and to maximize hit rate of the spiked compounds. A practical detection limit was established at 25 μg/kg. At this concentration, most compounds (17 out of 19) were detected as intact precursor ions, as fragments or as adducts. Only 2 irrelevant hits, probably natural compounds, were obtained. Limitations and possible practical use of the approach are discussed.Electronic supplementary materialThe online version of this article (10.1007/s00216-018-1028-4) contains supplementary material, which is available to authorized users.

Retrospective analysis for valproate screening targets with liquid chromatography–high resolution mass spectrometry with positive electrospray ionization: An omics‐based approach

“…The only prior knowledge was from parallel analysis, i.e., whether samples were positive or negative for VPA. The omics-based workflow resembles untargeted metabolomics workflows performed with LC-HRMS in identification of drug metabolites, 13,37 food contaminants, 38 and foodintake biomarkers. 39 Therefore, the potential targets were evaluated as binary classifiers, rather than by correlation analysis and multivariate analysis.…”

“…The omics-based workflow resembles untargeted metabolomics workflows performed with LC-HRMS in identification of drug metabolites, 13,37 food contaminants,38 and foodintake biomarkers 39. The omics-based workflow resembles untargeted metabolomics workflows performed with LC-HRMS in identification of drug metabolites, 13,37 food contaminants,38 and foodintake biomarkers 39.…”

An overview of chemical contaminants and other undesirable chemicals in alcoholic beverages and strategies for analysis

“…Although the aforementioned compound types still remain of interest, NTA is also applicable toward compounds that are unexpected and unregulated, NIAS, and unidentified compounds, and is useful in identifying abnormal signals within sample matrices (García Ibarra, Rodríguez Bernaldo de Quirós, Paseiro Losada, & Sendón, 2019). Although the targeted analytical food safety protocols are more passive in nature, NTA allows for a more proactive approach in determining potential hazards that are lesser known or have not been previously identified (Kunzelmann et al, 2018). NTA may be divided into two major approaches: (a) a broad, metabolomics-based approach and (2) suspect screening; this has also been termed as broad versus chivalrous NTA (Shao et al, 2019).…”

“…Analytical instruments utilized in NTA include MS, Nuclear Magnetic Resonance (NMR), FTIR, and other spectroscopic methods. Nondestructive methods such as FTIR or NMR certainly offer the advantage of ease in preparatory procedures and can provide precise, quantitative data, but fall short in terms of sensitivity, making the TA B L E 4 Comparison of MS based targeted analysis and nontargeted analysis techniques (including some information from Dom et al, 2018;Kunzelmann et al, 2018;Ribbenstedt, Ziarrusta, & Benskin, 2018) Targeted analysis…”

“…Beyond the issue of contaminants in alcohol—that is, undesirable substances without a functional purpose that are inadvertently introduced or produced—there is also the notable issue of adulterants. Unscrupulous manufacturers may engage in food fraud by adding illegal substances or substances in illegal quantities to food products, with the goal of increasing the quantity or apparent quality of the product; not only is this deception an unfair business practice, but it can have devastating impacts on human health (Kunzelmann, Winter, Åberg, Hellenäs, & Rosén, 2018). This presents a notable concern in the field of food analysis for quality control and safety, as underhanded producers are becoming knowledgeable about routine analytical techniques and are adopting craftier methods to evade detection (Ellis et al., 2012).…”