Background ions into exclusion list: A new strategy to enhance the efficiency of DDA data collection for high-throughput screening of chemical contaminations in food

Reproducibility in nontarget screening (NTS) of environmental emerging contaminants: Assessing different HLB SPE cartridges and instruments

Non-targeted screening (NTS) methods are integral in environmental research for detecting emerging contaminants. However, their efficacy can be influenced by variations in hydrophilic-lipophilic balance (HLB) solid phase extraction (SPE) cartridges and high-resolution mass spectrometry (HRMS) instruments across different laboratories. In this study, we scrutinized the influence of five HLB SPE cartridges (Nano, Weiqi, CNW, Waters, and J&K) and four LC-HRMS platforms (Agilent, Waters, Thermo, and AB SCIEX) on the identification of emerging environmental contaminants. Our results demonstrate that 87.6 % of the target compounds and over 59.6 % of the non-target features were consistently detected across all tested HLB cartridges, with an overall 71.2 % universally identified across the four LC-HRMS systems. Discrepancies in detection rates were primarily attributable to variations in retention time stability, mass stability of precursors and fragments, system cleanliness affecting fold change and p-values, and fragment response. These findings confirm the necessity of refining parameter criteria for NTS. Moreover, our study confirms the efficacy of the PyHRMS tool in analyzing and processing data from multiple instrumental platforms, reinforcing its utility for multi-platform NTS. Overall, our findings underscore the reliability and robustness of NTS methods in identifying potential water contaminants, while also highlighting factors that may influence these outcomes.

New insights into the bioaccessibility and metabolic fates of short-chain bioactive peptides in goat milk using the INFOGEST static digestion model and an improved data acquisition strategy

The metabolic fates of potentially bioactive short-chain peptides (SCPs; amino acid numbers between 2 and 4) in gastrointestinal digestion have received little attention due to their low concentration and broad suppression during high resolution mass spectrometry (HRMS) analysis. A tailored workflow integrating mesoporous magnetic solid phase extraction and a novel ion transmission strategy (data-dependent acquisition combined with both an inclusion list and an exclusion list followed by a data-independent acquisition) was used to profile the composition of SCPs during in vitro simulated digestion (LOQ 0.02 to 0.1 μg L^-1). A total of 47 dipeptides, 59 tripeptides, and 21 tetrapeptides were identified and quantified from 0.01 to 27.84 mg L^-1 (RSD ≤ 9.1%) based on parallel reaction monitoring and an internal standard method. The structural properties of stable SCPs resistant to intestinal digestion were determined by analysis of variance (p < 0.05), with a Pro residue at the C-terminal or penultimate position, a slightly greater negative charge at pH 7.0, and fewer C-terminal aliphatic and polar amino acids. SCPs' metabolic fates varied during digestion, but the overall trend of content change for either total or individual SCP increased as the digestion proceeded, and they were further assessed by a database-driven bioactivity search, which matched a wide variety of bioactivities with the predominance of dipeptidyl peptidase (DPP) IV and angiotensin-converting enzyme (ACE) inhibitors. This study facilitated the understanding of bioaccessibility of the food-derived SCPs and provided essential guidelines for the properties of conserved structure in vivo.

Potential biomarkers analysis and protein internal mechanisms by cold plasma treatment: Is proteomics effective to elucidate protein-protein interaction network and biochemical pathway?

New market trends of meat flavor, tenderness, and color quality indicators have prompted the research on meat preservation as a crucial topic to received attention. Present research about the effects of irradiation, cold plasma technology on meat is incomplete. There are strongly recommended that proteomics techniques be jointly to enhance the coverage of internal meat molecules for meat research. By identifying meat proteins, detecting biological functions, and quantifying the protein segments of specific meat biomarkers, which can be provided for the information of diagnostic components in preservative technologies. The current review provides scientific findings on various control strategies: (i) combine the data-independent acquisition to provide a reference for the meat molecular mechanism and rapid identification; (ii) design molecular networks biological functions assessment model; (iii) molecular investigations of cold plasma techniques and underlying mechanisms; (iv) explore the X-rays and γ-rays treatment in meat preservation and myoglobin change mechanism more comprehensively.

One sample multi-point calibration curve as a novel approach for quantitative LC-MS analysis: the quantitation of six aflatoxins in milk and oat-based milk as an example

Preparing of calibration curves are critical steps for accurate quantitative LC-MS bioanalysis. Traditional multi-sample external calibration curve (MSCC) is labor-intensive and prone to error. In this study, a novel strategy of one sample multi-point calibration curve (OSCC) using multiple isotopologue reaction monitoring (MIRM) was proposed and validated using LC-MS for the quantitation of six aflatoxins in milk and oat-based milk samples. The developed MIRM-OSCC methodology is comprehensively validated and the results indicated that the established method exhibits good performance in selectivity, sensitivity, accuracy and precision. Furthermore, the OSCC could realize sample dilution by monitoring the MIRM channel with less intensity for samples beyond the upper limit of quantification, without the need of sample dilution, which improves the assay throughput. Considering the advantages of excluding the MSCC preparation and sample dilution in OSCC, this strategy can be widely applied in various fields such as drugs, food safety and environmental analysis.

Enhanced Identification of Ginsenosides Simultaneously from Seven Panax Herbal Extracts by Data-Dependent Acquisition Including a Preferred Precursor Ions List Derived from an In-House Programmed Virtual Library

Data-dependent acquisition (DDA) is widely utilized for metabolite identification in natural product research and food science, which, however, can suffer from low coverage. A potential solution to improve DDA coverage is to include the precursor ions list (PIL). Here, we aimed to construct a PIL-containing DDA strategy based on an in-house library of ginsenosides (VLG) and identify ginsenosides simultaneously from seven Panax herbal extracts. VLG, combined with mass defect filtering, could efficiently screen the ginsenoside precursors and elaborate the separate PIL involved in DDA for each ginseng extract. Consequently, we could characterize 500 ginsenosides, including 176 ones with unknown masses. Using the Panax ginseng extract, the superiority of this strategy was embodied in targeting more known ginsenoside masses and newly acquiring the MS² spectra of 13 components. Conclusively, knowledge-based large-scale molecular prediction and PIL-DDA can represent a powerful targeted/untargeted strategy beneficial to novel natural compound discovery.