Principal component analysis of molecularly based signals from infant formula contaminations using LC-MS and NMR in foodomics

Nontargeted screening of veterinary drugs and their metabolites in milk based on mass defect filtering using liquid chromatography-high-resolution mass spectrometry

The development of nontargeted screening strategy for veterinary drugs and their metabolites is very important for food safety. In this study, a nontargeted screening strategy was developed to find the potentially hazardous substances based on mass defect filtering (MDF) using liquid chromatography-high-resolution mass spectrometry. First, the drug metabolites of 112 veterinary drugs from seven classes of antimicrobials were predicted. Second, three MDF models were established, including the traditional rectangular MDF, the enhanced parallelogram MDF, and the polygonal MDF. Finally, the strategy was applied to nontargeted screening of veterinary drugs in 36 milk samples. The polygonal MDF model based on the distribution area of parent drugs and their metabolites showed a better filtering effect. After removing food components and performing MDF, about 10% of the substances remained, and four veterinary drugs and six drug metabolites were discovered and identified, showing the effectiveness of this strategy. The nontargeted screening strategy can rapidly remove interfering substances and find the suspected compounds. It can also be used for nontargeted screening of veterinary drugs and their metabolites in other food matrices.

Pesticide residue intake from fruits and vegetables and alterations in the serum metabolome of women undergoing infertility treatment

BACKGROUND

Pesticide exposure is linked to a myriad of negative health effects; however, the mechanisms underlying these associations are less clear. We utilized metabolomics to describe the alterations in the serum metabolome associated with high and low pesticide residue intake from fruits and vegetables (FVs), the most common route of exposure in humans.

METHODS

This analysis included 171 women undergoing in vitro fertilization who completed a validated food frequency questionnaire and provided a serum sample during controlled ovarian stimulation (2007-2015). FVs were categorized as high or low-to-moderate pesticide residue using a validated method based on pesticide surveillance data from the USDA. We conducted untargeted metabolic profiling using liquid chromatography with high-resolution mass spectrometry and two chromatography columns. We used multivariable generalized linear models to identified metabolic features (p < 0.005) associated with high and low-to-moderate pesticide residue FV intake, followed by enriched pathway analysis.

RESULTS

We identified 50 and 109 significant features associated with high pesticide residue FV intake in the C18 negative and HILIC positive columns, respectively. Additionally, we identified 90 and 62 significant features associated with low-to-moderate pesticide residue FV intake in the two columns, respectively. Four metabolomic pathways were associated with intake of high pesticide residue FVs including those involved in energy, vitamin, and enzyme metabolism. 12 pathways were associated with intake of low-to-moderate pesticide residue FVs including cellular receptor, energy, intercellular signaling, lipid, vitamin, and xenobiotic metabolism. One energy pathway was associated with both high and low-to-moderate pesticide residue FVs.

CONCLUSIONS

We identified limited overlap in the pathways associated with intake of high and low-to-moderate pesticide residue FVs, which supports findings of disparate health effects associated with these two exposures. The identified pathways suggest there is a balance between the dietary antioxidant intake associated with FVs intake and heightened oxidative stress as a result of dietary pesticide exposure.

A Review on the Foodomics Based on Liquid Chromatography Mass Spectrometry

Due to the globalization of food production and distribution, the food chain has become increasingly complex, making it more difficult to evaluate unexpected food changes. Therefore, establishing sensitive, robust, and cost-effective analytical platforms to efficiently extract and analyze the food-chemicals in complex food matrices is essential, however, challenging. LC/MS-based metabolomics is the key to obtain a broad overview of human metabolism and understand novel food science. Various metabolomics approaches (e.g., targeted and/or untargeted) and sample preparation techniques in food analysis have their own advantages and limitations. Selecting an analytical platform that matches the characteristics of the analytes is important for food analysis. This review highlighted the recent trends and applications of metabolomics based on "foodomics" by LC-MS and provides the perspectives and insights into the methodology and various sample preparation techniques in food analysis.

Metabolomic Insights into the Effects of Breast Milk Versus Formula Milk Feeding in Infants

PURPOSE OF REVIEW

This review summarizes the latest scientific evidence for the presence of metabolomic differences between infants fed breast milk (I-BM) and infants fed formula milk (I-FM).

RECENT FINDINGS

Across the studies included in this review, a total of 261 metabolites were analyzed, of which 151 metabolites were reported as significantly associated with infant feeding modality (BM versus FM). However, taken as a whole, the relevant literature was notable both for methodological limitations, such as small sample sizes, and heterogeneity between the studies. This may be why many associations between infant metabolite profile and feeding modality have not replicated across studies. To our knowledge, this is the first review to integrate the available literature on metabolomic differences between I-BM versus I-FM. This narrative review synthesized the data across studies and identified those metabolites which show the most robust associations with infant feeding modality. Methodological limitations of the current studies are identified, followed by recommendations for how to address these in future studies.

Reliable, accessible and transferable method for the quantification of flavanols and procyanidins in foodstuffs and dietary supplements

Liquid chromatography coupled with fluorescence detection for accurate and precise determination of cocoa flavanol monomers and procyanidins in cocoa-based products.

Nontargeted Detection Methods for Food Safety and Integrity

Nontargeted workflows for chemical hazard analyses are highly desirable in the food safety and integrity fields to ensure human health. Two different analytical strategies, nontargeted metabolomics and chemical database filtering, can be used to screen unknown contaminants in food matrices. Sufficient mass and chromatographic resolutions are necessary for the detection of compounds and subsequent componentization and interpretation of candidate ions. Analytical chemistry–based technologies, including gas chromatography–mass spectrometry (GC-MS), liquid chromatography–mass spectrometry (LC-MS), nuclear magnetic resonance (NMR), and capillary electrophoresis–mass spectrometry (CE-MS), combined with chemometrics analysis are being used to generate molecular formulas of compounds of interest. The construction of a chemical database plays a crucial role in nontargeted detection. This review provides an overview of the current sample preparation, analytical chemistry–based techniques, and data analysis as well as the limitations and challenges of nontargeted detection methods for analyzing complex food matrices. Improvements in sample preparation and analytical platforms may enhance the relevance of food authenticity, quality, and safety.