Nontargeted Screening Method for Illegal Additives Based on Ultrahigh-Performance Liquid Chromatography-High-Resolution Mass Spectrometry

Fragmentation characteristics-based nontargeted screening method of exogenous chemical residues in animal-derived foods using reversed-phase and hydrophilic interaction liquid chromatography-high-resolution mass spectrometry

Fragmentation characteristics are crucial for nontargeted screening to discover and identify unknown exogenous chemical residues in animal-derived foods. In this study, first, fragmentation characteristics of 51 classes of exogenous chemical residues were summarized based on experimental mass spectra of standards in reversed-phase and hydrophilic interaction liquid chromatography-high-resolution mass spectrometry (MS) and mass spectra from the MassBank of North America (MoNA) library. According to the proportion of fragmentation characteristics to the total number of chemical residues in each class, four screening levels were defined to classify 51 classes of chemical residues. Then, a nontargeted screening method was developed based on the fragmentation characteristics. The evaluation results of 82 standards indicated that more than 90 % of the chemical residues with MS/MS spectra can be identified at concentrations of 100 and 500 μg/kg, and about 80 % can be identified at 10 μg/kg. Finally, the nontargeted screening method was applied to 16 meat samples and 21 egg samples as examples. As a result, eight chemical residues and transformation products (TPs) of 5 classes in the exemplary samples were found and identified, in which 3 TPs of azithromycin were identified by fragmentation characteristics-assisted structure interpretation. The results demonstrated the practicability of the nontargeted screening method for routine risk screening of food safety.

Advanced Mass Spectrometry-Based Biomarker Identification for Metabolomics of Diabetes Mellitus and Its Complications

Over the years, there has been notable progress in understanding the pathogenesis and treatment modalities of diabetes and its complications, including the application of metabolomics in the study of diabetes, capturing attention from researchers worldwide. Advanced mass spectrometry, including gas chromatography-tandem mass spectrometry (GC-MS/MS), liquid chromatography-tandem mass spectrometry (LC-MS/MS), and ultra-performance liquid chromatography coupled to electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC-ESI-Q-TOF-MS), etc., has significantly broadened the spectrum of detectable metabolites, even at lower concentrations. Advanced mass spectrometry has emerged as a powerful tool in diabetes research, particularly in the context of metabolomics. By leveraging the precision and sensitivity of advanced mass spectrometry techniques, researchers have unlocked a wealth of information within the metabolome. This technology has enabled the identification and quantification of potential biomarkers associated with diabetes and its complications, providing new ideas and methods for clinical diagnostics and metabolic studies. Moreover, it offers a less invasive, or even non-invasive, means of tracking disease progression, evaluating treatment efficacy, and understanding the underlying metabolic alterations in diabetes. This paper summarizes advanced mass spectrometry for the application of metabolomics in diabetes mellitus, gestational diabetes mellitus, diabetic peripheral neuropathy, diabetic retinopathy, diabetic nephropathy, diabetic encephalopathy, diabetic cardiomyopathy, and diabetic foot ulcers and organizes some of the potential biomarkers of the different complications with the aim of providing ideas and methods for subsequent in-depth metabolic research and searching for new ways of treating the disease.

Development and Application of a Comprehensive Nontargeted Screening Strategy for Aristolochic Acid Analogues

Aristolochic acid analogs (AAAs) are naturally occurring carcinogenic and toxic compounds that pose a safety threat to pharmaceuticals and the environment. It is challenging to screen AAAs due to their lack of characteristic mass spectral fragmentation and their presence of structural diversity. A comprehensive nontargeted screening strategy was proposed by taking into account diverse factors and incorporating various self-developed techniques, and a Python3-based toolkit called AAAs_finder was developed for its implementation. The main procedures consist of virtual structure and ultraviolet and visible (UV) spectra database creation, exact mass and UV spectra-based suspect data extraction, tandem mass spectra (MS/MS) anthropomorphic interpretation, and multicondition retention time (RT) prediction-based candidate structures ranking. To initially assess screening feasibility, eight hypothetical unknown samples were subjected to nontargeted screening using the AAAs_finder toolkit and two other advanced tools. The results showed that the former successfully identified all, while the latter two only managed to identify two and three, respectively, indicating that our strategy was more feasible. After that, the strategy was carefully evaluated for false positives and false negatives, instrument dependence, reproducibility, and sensitivity. After the evaluation, the strategy was successfully applied to the screening of AAAs in real samples, such as herbal medicine, spiked soil, and water. Overall, this study proposed a nontargeted screening strategy and toolkit independent of characteristic mass spectral fragmentation and able to overcome challenges posed by structural diversity for the AAAs screening, which is also valuable for other classes of compounds.

A novel endogenous retention-index for minimizing retention-time variations in metabolomic analysis with reversed-phase ultrahigh-performance liquid-chromatography and mass spectrometry

Consistent retention time (tR) of metabolites is vital for identification in metabolomic analysis with ultrahigh-performance liquid-chromatography (UPLC). To minimize inter-experimental tR variations from the reversed-phase UPLC-MS, we developed an endogenous retention-index (endoRI) using in-sample straight-chain acylcarnitines with different chain-length (LC, C0-C26) without additives. The endoRI-corrections reduced the tR variations caused by the combined changes of mobile phases, gradients, flow-rates, elution time, columns and temperature from up to 5.1 min-0.2 min for most metabolites in a model metabolome consisting of 91 metabolites and multiple biological matrices including human serum, plasma, fecal, urine, A549 cells and rabbit liver extracts. The endoRI-corrections also reduced the inter-batch and inter-platform tR variations from 1.5 min to 0.15 min for 95 % of detected features in the above biological samples. We further established a quantitative model between tR and LC for predicting tR values of acylcarnitines when absent in samples. This makes it possible to compare metabolites' tR from different tR databases and the UPLC-based metabolomic data from different batches.

Using UHPLC-HRMS-based comprehensive strategy to efficiently and accurately screen and identify illegal additives in health-care foods

Accurately and high-thoroughly screening illegal additives in health-care foods continues to be a challenging task in routine analysis for the ultrahigh performance liquid chromatography-high resolution mass spectrometry based techniques. In this work, we proposed a new strategy to identify additives in complex food matrices, which consists of both experimental design and advanced chemometric data analysis. At first, reliable features in the analyzed samples were screened based on a simple but efficient sample weighting design, and those related to illegal additives were screened with robust statistical analysis. After the MS¹ in-source fragment ion identification, both MS¹ and MS/MS spectra were constructed for each underlying compound, based on which illegal additives can be precisely identified. The performance of the developed strategy was demonstrated by using mixture and synthetic sample datasets, indicating an improvement of data analysis efficiency up to 70.3 %. Finally, the developed strategy was applied for the screening of unknown additives in 21 batches of commercially available health-care foods. Results indicated that at least 80 % of false-positive results can be reduced and 4 additives were screened and confirmed.

Screening strategy for 1210 exogenous chemicals in serum by two-dimensional liquid chromatography-mass spectrometry

Humans are at risk of exogenous exposure to exogenous chemicals. Challenges exist for the comprehensive monitoring of residues with different physical and chemical properties in serum. Here, an on-line two-dimensional liquid chromatography (2D-LC) - high resolution mass spectrometry system (HRMS) was developed, expanding the range of the partition coefficient in octanol/water of the residue analysis from -8 to 12. A high-coverage serum residue screening strategy was further designed by integrating 2D-LC system with HRMS full MS/data independent acquisition and automatic spectral library searching. This strategy enables to simultaneously screen 1210 pesticides, veterinary/human drugs, other chemical pollutants and their metabolites in serum with a single analysis. Method validation showed 92% and 81% of 1022 residues spiked in serum could be detected at 50 ng/mL and 5 ng/mL, respectively. The developed method was applied to the analysis of 24 separately pooled serum samples, 58 suspect residues were found, some of them were detected at high frequencies over than 50%. Among them, 4,6-Dinitro-O-cresol and probable carcinogenic folpet are highly toxic, and cimaterol is banned in China. Collectively, this study developed a 2D-LC-HRMS -based screening strategy for screening pesticides, veterinary/human drugs, and other chemical pollutants in serum, it is helpful for studying the effect of exogenous exposures on human health.

Magnetic amino-rich hyper-crosslinked polymers for fat-rich foodstuffs pretreatment in nontargeted analysis of chemical hazards

Nontargeted analysis for chemical hazards is highly desirable in controlling food safety to ensure human health. As the dominating interference in fat-rich foodstuffs, lipids removal is a great challenge in sample pretreatment. Herein, diverse lipids from both animal and vegetable oils are effectively removed and 565 chemical hazards with various physicochemical properties are used for method validation. These benefits are from the designed magnetic amino-rich hyper-crosslinked core-shell polymeric composites (Fe₃O₄@poly(MAAM-co-EGDMA)) and the application of an auto extraction system. Among them, the amino groups are the key factors for lipid removal. Theoretical calculations, isothermal titration calorimetry (ITC), and functional monomer replacement demonstrated that the mechanisms to universally capture free fatty acids (FFAs) and triglycerides (TGs) are electrostatic interaction and supplemented by hydrogen bonding. Overall, this work highlights the great application potentials of polymeric adsorbents as sample pretreatment materials for nontargeted analysis in food safety.

Identification of mouse metabolic variations related to patulin-induced acute and subacute hepatotoxicity by ultra-high-performance liquid chromatography high-resolution mass spectrometry

Patulin (PAT), a toxin produced by molds in fruits and related products, has caused frequent food poisoning incidents worldwide. However, its potential mechanism of hepatotoxicity remains presently unclear. Herein, we intragastrically administered the C57BL/6J mice with 0, 1, 4, and 16 mg/kg b.wt of PAT on a single occasion (acute model), and 0, 50, 200, and 800 μg/kg b.wt of PAT daily over two weeks (subacute model). Assessments of histopathology and aminotransferase activities confirmed that significant hepatic damages were induced. Metabolic profiling on the liver using ultra-high-performance liquid chromatography high-resolution mass spectrometry discovered 43 and 61 differential metabolites in two models, respectively. Notably, acute and subacute models shared the common 18 differential metabolites, among which N-acetyl-leucine, inosine, 2-O-methyladenosine, PC 40:7, PC 38:6, and PC 34:2 could be regarded as the biomarkers indicative of PAT exposure. Moreover, analysis of metabolic pathways demonstrated that pentose phosphate pathway and purine metabolism were the main altered pathways in the acute model. Nevertheless, more pathways related to amino acids were affected in the subacute model. These results reveal the comprehensive influence of PAT on hepatic metabolism and provide a deeper understanding of the hepatotoxicity mechanism of PAT.

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.

Metabolomics Approach on Non-Targeted Screening of 50 PPCPs in Lettuce and Maize

The metabolomics approach has proved to be promising in achieving non-targeted screening for those unknown and unexpected (U&U) contaminants in foods, but data analysis is often the bottleneck of the approach. In this study, a novel metabolomics analytical method via seeking marker compounds in 50 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked into lettuce and maize matrices was developed, based on ultrahigh-performance liquid chromatography-tandem mass spectrometer (UHPLC-MS/MS) output results. Three concentration groups (20, 50 and 100 ng mL-1) to simulate the control and experimental groups applied in the traditional metabolomics analysis were designed to discover marker compounds, for which multivariate and univariate analysis were adopted. In multivariate analysis, each concentration group showed obvious separation from other two groups in principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) plots, providing the possibility to discern marker compounds among groups. Parameters including S-plot, permutation test and variable importance in projection (VIP) in OPLS-DA were used for screening and identification of marker compounds, which further underwent pairwise t-test and fold change judgement for univariate analysis. The results indicate that marker compounds on behalf of 50 PPCPs were all discovered in two plant matrices, proving the excellent practicability of the metabolomics approach on non-targeted screening of various U&U PPCPs in plant-derived foods. The limits of detection (LODs) for 50 PPCPs were calculated to be 0.4~2.0 µg kg-1 and 0.3~2.1 µg kg-1 in lettuce and maize matrices, respectively.

Comprehensively screening of citric acid ester (CAE) plasticizers in Chinese foodstuffs, and the food-based assessment of human exposure risk of CAEs

An increasing number of studies on the toxicities of citric acid esters (CAEs)-a class of so-called "safe" alternative plasticizers-have highlighted the urgent need to understand their contamination profiles in foodstuffs and the corresponding potential risks to human health. This study determined the concentrations of 8 target CAEs in 105 foodstuff samples, grouped into 6 food categories, collected from Nanjing City, China, in 2020. All eight CAEs were detected in at least one of the analyzed samples and had detection frequencies (DFs) of 5-47%. The DFs and distribution profiles of the target CAEs varied among different food categories; for example, cereals had the highest DF (92%), while meat/fish contained the highest mean total concentration of CAEs (8.35 ng/g wet weight (ww)). Among the target CAEs, acetyl tributyl citrate (ATBC) had the highest DF (47%), and tributyl citrate (TBC) exhibited the highest mean concentration (1.24 ng/g ww). Based on the food ingestion route, the estimated total daily intake (EDI) values of the target CAEs for adults under average- and high-exposure scenarios were 38.3 ng/kg of body weight (bw) and 111 ng/kg bw, respectively, which were attributed to the high percentage contributions of TBC (50.6%) and ATBC (23.7%). In addition, a suspect and characteristic fragment-dependent screening strategy was applied to the foodstuff data, and a novel CAE, monoethyl citrate (MEC, CAS: 4552-00-5), with a DF of 34% was tentatively identified. Overall, this study provides novel and comprehensive information regarding the pollution status of CAEs in foodstuffs.

Nontargeted screening method for veterinary drugs and their metabolites based on fragmentation characteristics from ultrahigh-performance liquid chromatography-high-resolution mass spectrometry

Nontargeted screening of both veterinary drugs and their metabolites is important for comprehensive safety evaluation of animal-derived foods. In this study, a novel nontargeted screening strategy was developed for veterinary drugs and their metabolites based on fragmentation characteristics from ultrahigh-performance liquid chromatography-high-resolution mass spectrometry. First, an in-house database of mass spectra including 3,710 veterinary drugs and their metabolites was constructed. Second, fragmentation characteristics of parent drugs and their metabolites in mass spectrometry were investigated and summarized. Then, a nontargeted screening procedure was established based on fragmentation characteristics to screen unknown parent drugs and their metabolites. Finally, the strategy was applied to 33 egg samples, and four veterinary drugs and three drug metabolites were determined and identified. These results showed that the developed strategy can realize suspect and nontargeted screening of veterinary drugs and their metabolites, and can also be applied to other animal-derived foods.

Metabolomics-based non-targeted screening analysis of 34 PPCPs in bovine and piscine muscles

The metabolomics-based analytical strategy has showed superiority on the non-targeted screening of contaminants, especially for unknown and unexpected (U&U) contaminants in the field of food safety, but data analysis is often the bottleneck of the strategy. In this study, a novel metabolomics-based analytical method via searching for marker compounds was developed on the basis of ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) results to accurately, rapidly and comprehensively achieve the non-targeted screening of 34 pharmaceutical and personal care products (PPCPs) as U&U contaminants spiked in bovine and piscine muscle matrices. Three concentration groups (20, 50 and 100 ng mL^-1) were intentionally designed to simulate the control and experimental groups for the discovery of marker compounds, for which multivariate and univariate analyses were adopted. In multivariate analysis, each concentration group was fully separated from the other two groups in PCA and OPLS-DA plots, laying a foundation to distinguish marker compounds among groups. The S-plot, permutation and variable importance in projection (VIP) in OPLS-DA were employed to screen and identify marker compounds, which were further verified by pairwise t-test and fold change judgement in univariate analysis. The results indicate that 34 PPCPs spiked in two muscle matrices were all identified as marker compounds, proving the validity and practicability of this novel metabolomics-based non-targeted screening method, which will exhibit great superiority and broad application prospects, especially in the face of massive PPCPs and various animal matrices in the field of food safety control. In addition, the limits of detection (LODs) for 34 PPCPs were calculated to be 0.2-2.6 μg kg^-1 and 0.3-2.1 μg kg^-1 in bovine and piscine muscle matrices, respectively.

Data analysis strategies for the characterization of chemical contaminant mixtures. Fish as a case study

Thousands of chemicals are potentially contaminating the environment and food resources, covering a wide spectrum of molecular structures, physico-chemical properties, sources, environmental behavior and toxic profiles. Beyond the description of the individual chemicals, characterizing contaminant mixtures in related matrices has become a major challenge in ecological and human health risk assessments. Continuous analytical developments, in the fields of targeted (TA) and non-targeted analysis (NTA), have resulted in ever larger sets of data on associated chemical profiles. More than ever, the implementation of advanced data analysis strategies is essential to elucidate profiles and extract new knowledge from these large data sets. Specifically focusing on the data analysis step, this review summarizes the recent progress in integrating data analysis tools into TA and NTA workflows to address the challenging characterization of chemical mixtures in environmental and food matrices. As fish matrices are relevant in both aquatic pollution and consumer exposure perspectives, fish was chosen as the main theme to illustrate this review, although the present document is equally relevant to other food and environmental matrices. The key features of TA and NTA data sets were reviewed to illustrate the challenges associated with their analysis. Advanced filtering strategies to mine NTA data sets are presented, with a particular focus on chemical filters and discriminant analysis. Further, the applications of supervised and unsupervised multivariate analysis methods to characterize exposure to chemical mixtures, and their associated challenges, is discussed.

Nontargeted metabolomics-based mapping urinary metabolic fingerprints after exposure to acrylamide

Acrylamide classified as a probable carcinogen to humans is a high production volume chemical in industrial applications released to aquatic and environmental ecosystems, and also widely found in the thermal processing of starch-rich foods. To gain insight into the urinary metabolomics that may induce physiological responses stimulated by acrylamide, rats were orally administered with a single dose of 13C3-acrylamide (10 mg/kg bw) in the treatment group and urine samples were continuously collected every 2 h during the first 18 h and every 3 h during the period from 18 h to 36 h. A reliable nontargeted screening method for the analysis of urinary metabolomics in rats was developed using ultra-high performance liquid chromatography coupled to quadrupole-Orbitrap high-resolution mass spectrometry. All metabolites in urine of rats receiving isotope-labeled acrylamide were screened by validated orthogonal partial least squares-discriminant analyses compared to the animals in the control group, while exposure biomarkers were further confirmed according to the characteristic fragmentation rules and time-dependent profiles. Here we identified 2 new specific exposure biomarkers, named N-acetyl-S-(2-carbamoyl-2-hydroxyethyl)-L-cysteine-sulfoxide and N-acetyl-S-(2-carboxyl)-L-cysteine, compared to 4 currently acknowledged mercapturic acid adducts of acrylamide. In addition, our findings on analysis of acrylamide metabolic pathway and identification of exposure biomarkers confirmed that acrylamide could significantly affect energy metabolism and amino acid metabolism by the Kyoto Encyclopedia of Genes and Genomes pathway analysis for key metabolites. Homocysteine thiolactone and hypoxanthine may be potential biomarkers for the cardiotoxicity, while methionine sulfoxide, hippuric acid and melatonin may be specifically related to the neurotoxicity. Thus, the current study provided new evidence on the identification of emerging exposure biomarkers and specific signature metabolites related to the toxicity of acrylamide, and shed light on how acrylamide affected energy and amino acid metabolism by further mapping urinary metabolic fingerprints.

An Automated Methodology for Non-targeted Compositional Analysis of Small Molecules in High Complexity Environmental Matrices Using Coupled Ultra Performance Liquid Chromatography Orbitrap Mass Spectrometry

The life-critical matrices of air and water are among the most complex chemical mixtures that are ever encountered. Ultrahigh-resolution mass spectrometers, such as the Orbitrap, provide unprecedented analytical capabilities to probe the molecular composition of such matrices, but the extraction of non-targeted chemical information is impractical to perform via manual data processing. Automated non-targeted tools rapidly extract the chemical information of all detected compounds within a sample dataset. However, these methods have not been exploited in the environmental sciences. Here, we provide an automated and (for the first time) rigorously tested methodology for the non-targeted compositional analysis of environmental matrices using coupled liquid chromatography-mass spectrometric data. First, the robustness and reproducibility was tested using authentic standards, evaluating performance as a function of concentration, ionization potential, and sample complexity. The method was then used for the compositional analysis of particulate matter and surface waters collected from worldwide locations. The method detected >9600 compounds in the individual environmental samples, arising from critical pollutant sources, including carcinogenic industrial chemicals, pesticides, and pharmaceuticals among others. This methodology offers considerable advances in the environmental sciences, providing a more complete assessment of sample compositions while significantly increasing throughput.

A mathematical method for calibrating the signal drift in liquid chromatography - mass spectrometry analysis

Liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) has become the most versatile analytical tool for profiling small-molecule compounds and increasingly been applied in many fields. Nevertheless, LC-MS based quantification still face some challenges, such as signal drift in LC-MS, which may affect the validity of the obtained data and lead to misinterpretation of biological results. Here, we established a calibration method known as "RIM" to compensate the signal drift of LC-MS. To this end, a mixture of d₄-2-dimethylaminoethylamine (d₄-DMED)-coded normal fatty acids (C5-C23) was used as calibrants to construct RIM calibration. With the addition of calibrants, not only the MS signal drift, but also the mass accuracy and LC retention time can be calibrated, thereby improving the reliability of quantitative data. The effectiveness of RIM was carefully validated using a human serum extract spiked with 34 standards and then RIM was applied for rat brain untargeted metabolome research. In addition, to expand the functionality and flexibility of RIM for data handling, we generated a MATLAB-based RIM program, which implements the above concepts and allows automatic data process. Taken together, the proposed RIM method has potential application in large-scale quantitative study of complex samples.

High-Coverage Screening of Sulfonamide Metabolites in Goat Milk by Magnetic Doped S Graphene Combined with Ultrahigh-Performance Liquid Chromatography-High-Resolution Mass Spectrometry

Currently, there are more than 1000 varieties of synthetic sulfonamides universally used as antibiotics causing severe results of potential carcinogenicity and drug resistance for human health due to excessive residue of animal-derived food. A facile and novel approach for untargeted screening of sulfonamides (SAs) and metabolites was proposed based on magnetic solid-phase extraction-ultrahigh-performance liquid chromatography-tandem high-resolution mass spectrometry (MSPE-UHPLC-HRMS). Compared with QuEChERS without the clean-up procedure and SPE in terms of matrix effect and absolute recovery, magnetic doped S graphene (S-doping level: 2.82%) synthesized via a solid-state microwave approach and the aggregation wrap mechanism was used as a novel adsorbent for nonspecific extraction of desired analytes by the noncovalent interaction between electron-deficient thiophene sulfur and electron donors such as amino or amide as well as π-π stacking interactions. Combined with variable data-independent acquisition, characteristic fragment-ion filtering (m/z 156.01138 or m/z 108.04439) and assignment of extracted-ion chromatograms of marked fragment ions were successfully utilized to screen the desired analytes and subsequently confirmed with the availability of reference standards. The optimized and validated approach for spiked 26 SAs and 9 metabolites in control goat milk demonstrated satisfactory accuracy (80.1-112.6%) and precision (RSDs < 6.4%) for matrix-matched standard addition. After applying suspect goat milk samples, untargeted SA analytes including sulfanilamide or an N⁴-acetylsulfamethazine metabolite with concentration ranging from 66.3 to 398.5 ng L^-1 were determined in 5 of 45 goat milk samples.

A chemometric strategy for accurately identifying illegal additive compounds in health foods by using ultra-high-performance liquid chromatography coupled to high resolution mass spectrometry

The accurate identification of unknown illegal additive compounds in complex health foods continues to be a challenging task in routine analysis, because massive false positive results can be screened with ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry-based untargeted techniques and must be manually filtered out. To address this problem, we developed a chemometric-based strategy, in which data analysis was first performed by using XCMS, MS-DIAL, Mzmine2, and AntDAS2, to select those that provided acceptable results to extract common features (CFs), which can be detected by all of the selected methods. Then, CFs whose contents were significantly higher in the suspected illegal additive group were screened. Isotopic, adduct, and neutral loss ions were marked based on the CFs by using a new adaptive ion annotation algorithm. Fragment ions originating from the same compound were identified by using a novel fragment ion identification algorithm. Finally, a respective mass spectrum was constructed for each screened compound to benefit compound identification. The developed strategy was confirmed by using a complex Chinese health food, Goujiya tea. The features of all illegal additive compounds were precisely screened by the developed strategy, and massive false positive features from the current data analysis method were greatly reduced. The constructed respective mass spectra can benefit compound identification and avoid the risk of identifying ions from the same illegal compound as different compounds. Moreover, unknown compounds that are contained in an illegal compound library can be screened.

Stochastic dynamic mass spectrometric quantification of steroids in mixture - Part II

This paper deals with quantification of the following steroids in mixture: hydrocortisone (1), deoxycorticosterone (2), progesterone (3) and methyltestosterone (4) by means of mass spectrometry and implementing our innovative stochatic dynamic functional relationship between the analyte concentration in solution and the experimental variable intensity. The mass spectrometric data are correlated independently using chromatography. Chemometric analysis is carried out.

Technical Overview of Orbitrap High Resolution Mass Spectrometry and Its Application to the Detection of Small Molecules in Food (Update Since 2012)

Food safety and quality issues are becoming increasingly important and attract much attention, requiring the development of better analytical platforms. For example, high-resolution (especially Orbitrap) mass spectrometry simultaneously offers versatile functions such as targeted/non-targeted screening while providing qualitative and quantitative information on an almost unlimited number of analytes to facilitate routine analysis and even allows for official surveillance in the food field. This review covers the current state of Orbitrap mass spectrometry (OMS) usage in food analysis based on research reported in 2012-2019, particularly highlighting the technical aspects of OMS application and the achievement of OMS-based screening and quantitative analysis in the food field. The gained insights enhance our understanding of state-of-the-art high-resolution mass spectrometry and highlight the challenges and directions of future research.

FUNCTIONAL METABOLOMICS DECIPHER BIOCHEMICAL FUNCTIONS AND ASSOCIATED MECHANISMS UNDERLIE SMALL-MOLECULE METABOLISM

Metabolism is the collection of biochemical reactions enabled by chemically diverse metabolites, which facilitate different physiological processes to exchange substances and synthesize energy in diverse living organisms. Metabolomics has emerged as a cutting-edge method to qualify and quantify the metabolites in different biological matrixes, and it has the extraordinary capacity to interrogate the biological significance that underlies metabolic modification and modulation. Liquid chromatography combined with mass spectrometry (LC/MS), as a robust platform for metabolomics analysis, has increased in popularity over the past 10 years due to its excellent sensitivity, throughput, and versatility. However, metabolomics investigation currently provides us with only phenotype data without revealing the biochemical functions and associated mechanisms. This limitation indeed weakens the core value of metabolomics data in a broad spectrum of the life sciences. In recent years, the scientific community has actively explored the functional features of metabolomics and translated this cutting-edge approach to be used to solve key multifaceted questions, such as disease pathogenesis, the therapeutic discovery of drugs, nutritional issues, agricultural problems, environmental toxicology, and microbial evolution. Here, we are the first to briefly review the history and applicable progression of LC/MS-based metabolomics, with an emphasis on the applications of metabolic phenotyping. Furthermore, we specifically highlight the next era of LC/MS-based metabolomics to target functional metabolomes, through which we can answer phenotype-related questions to elucidate biochemical functions and associated mechanisms implicated in dysregulated metabolism. Finally, we propose many strategies to enhance the research capacity of functional metabolomics by enabling the combination of contemporary omics technologies and cutting-edge biochemical techniques. The main purpose of this review is to improve the understanding of LC/MS-based metabolomics, extending beyond the conventional metabolic phenotype toward biochemical functions and associated mechanisms, to enhance research capability and to enlarge the applicable scope of functional metabolomics in small-molecule metabolism in different living organisms.

Analytical methods for mixed organic chemical residues and contaminants in food

Developing methods that can analyze multiple categories of organic chemical residues such as pesticides, veterinary drugs, mycotoxins, human drugs, and environmental contaminants in food with a single analytical procedure is a growing trend. These methods for mixed organic chemical residues and contaminants focus on the chemical properties of these analytes rather than how they are used and adulterate the food supply. This paper highlights recently published methods for mixed residue and contaminant methods in food including advances in technology (instrumental hardware, data processing programs, and sample cleanup) that allow for a larger number of compounds to be monitored simultaneously. The factors that determine the scope, or number and type of analytes in a given method, including needs for specific food commodities, complexity of the analytical procedure, and the intended purpose (qualitative vs quantitative analysis) will be examined. Although there are clear advantages to expanding the number of unwanted chemicals being monitored in the global food supply, challenges to developing and implementing mixed organic residue and contaminant methods will also be discussed. Going forward, it will be important to implement these methods to more thoroughly protect the food supply for a wide variety of targeted and non-targeted chemical residues and contaminants while also having the regulatory framework in place to effectively manage the results of these comprehensive analyses. Graphical abstract.

Sensitive Untargeted Screening of Nerve Agents and Their Degradation Products Using Liquid Chromatography-High Resolution Mass Spectrometry

Nerve agents (NAs) are notorious chemical warfare agents that pose a serious threat to national security and public health. The total number of theoretical chemicals of NAs and their degradation products (DPs) exceeds 410 000, according to 1.A.01-1.A.03 in the Schedules of Chemicals of the Chemical Weapons Convention, which poses great challenges for identification and verification. A three-step integrated untargeted screening strategy was developed based on high-resolution mass spectrometry. First, an extensible homemade library for targeted screening of common classical agents was established. Second, a set of in-source collision-induced dissociation mass spectrometry (MS)-alerting ions was extracted and concluded based on fragmentation behavior studies, which included 40 specific alerting ions and 10 types of characteristic structural fragments from total NAs and their DPs. A novel "alerting ion" searching method was developed to rapidly and sensitively screen whether or not nerve agent-related compounds were present and of which type they were. Third, we built a theoretical exact mass database including 202 accurate masses or molecular formulas, which could cover all structural possibilities of the NAs and their DPs. Comprehensively, the elemental composition of pseudomolecular ions, fragment ions, MS/MS spectra, and isotope pattern information were obtained from the full scan MS/data dependent-MS² experiments and elucidated for identification of the candidates selected in the screening step. This strategy was successfully applied to the identification of unknown chemicals in real samples with good stability and a low limit of detection of 1-10 ng/mL. These procedures are applicable for trace forensic investigations in cases of the alleged use of nerve agents.

Preliminary Study to Develop an Alternative Method for the Non-targeted Determination of Xenobiotics in Food by Means of Ultra High Performance Liquid Chromatography Coupled to High Resolution and Accuracy Mass Spectrometry

This preliminary study describes the use of high resolution and accuracy mass spectrometry techniques combined with new generation chemical software products for detecting and identifying contaminants in food commodities. As a first step, the extracts of routine target analysis samples (obtained in our official laboratory responsible for food residues control) were acquired and processed with this method in order to search unknown and non-targeted contaminants in food. In order to verify the feasibility of the presented method, the research has been firstly addressed to untargeted pesticides and their metabolites in stone fruits commodities and tomatoes. The differential analysis carried with Compound Discoverer 2.0 between the investigated unknown sample and the blank matrix sample allowed to remove all the matrix molecular components; Aggregated Computational Toxicology Resource (ACToR) helped to understand and predict chemical interpretation of substances. The acquisition in FullScan-AIF and FullScan-ddMS2 allowed the clear detection and identification of isobaric compounds such as quinalphos and phoxim. In order to verify that the proposed method is suitable to the scope of application, the main points of SANTE/11813/2017 Document have been followed. The results demonstrate that no false positives and no false negatives have been detected from the analysis of samples spiked with 55 pesticides at 0.010 and 0.10 mg kg−1. This preliminary study has been also tested with a Proficiency Test (EUPT-FV-SM08) and, according to EUPT-FV-SM08 Final Report, our laboratory has been included in the 67% (56) that clearly detected over 70% pesticides. Finally, this method has been extended to other matrices and contaminants.

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.

Perspectives on Liquid Chromatography-High-Resolution Mass Spectrometry for Pesticide Screening in Foods

This perspective discusses the use of liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS) for multiresidue analysis of pesticides in foods and agricultural commodities. HRMS has the important distinction and advantage of mass-resolving power and, therefore, requires different concepts, experiments, and guidance for screening, identification, and quantitation of pesticides in complex food matrices over triple quadrupole mass spectrometry. HRMS approaches for pesticide screening, including full-scan experiments in conjunction with tandem mass spectrometry (MS/MS) experiments, are described. This approach results in the generation of chromatographic retention times and high-resolution mass spectra with accurate mass measurements that can be used to create compound databases. New data processing tools can create an efficient and optimized screening approach that can speed the analysis and identification of compounds, reduce the need for chemical standards, and harmonize pesticide analytical procedures.

Development of a High Coverage Pseudotargeted Lipidomics Method Based on Ultra-High Performance Liquid Chromatography-Mass Spectrometry

Lipid coverage is crucial in comprehensive lipidomics studies challenged by high diversity in lipid structures and wide dynamic range in lipid levels. Current state-of-the-art lipidomics technologies are mostly based on mass spectrometry (MS), including direct-infusion MS, chromatography-MS, and matrix-assisted laser desorption ionization (MALDI) imaging MS, each with its pros and cons. Due to the need or favorability for measurement of isomers and isobars, chromatography-MS is preferable for lipid profiling. The ultra-high performance liquid chromatography-high resolution mass spectrometry (UHPLC-HRMS)-based nontargeted lipidomics approach and UHPLC-tandem MS (UHPLC-MS/MS)-based targeted approach are two representative methodological platforms for chromatography-MS. In the present study, we developed a high coverage pseudotargeted lipidomics method combining the advantages of nontargeted and targeted lipidomics approaches. The high coverage of lipids was achieved by integration of the detected lipids derived from nontargeted UHPLC-HRMS lipidomics analysis of multiple matrices (e.g., plasma, cell, and tissue) and the predicted lipids speculated on the basis of the structure and chromatographic retention behavior of the known lipids. A total of 3377 targeted lipid ion pairs with over 7000 lipid molecular structures were defined. The pseudotargeted lipidomics method was well validated with satisfactory analytical characteristics in terms of linearity, precision, reproducibility, and recovery for lipidomics profiling. Importantly, it showed better repeatability and higher coverage of lipids than the nontargeted lipidomics method. The applicability of the developed pseudotargeted lipidomics method was testified in defining differential lipids related to diabetes. We believe that comprehensive lipidomics studies will benefit from the developed high coverage pseudotargeted lipidomics approach.

Suspect Screening and Regulatory Databases: A Powerful Combination To Identify Emerging Micropollutants

This study demonstrates that regulatory databases combined with the latest advances in high resolution mass spectrometry (HRMS) can be efficiently used to prioritize and identify new, potentially hazardous pollutants being discharged into the aquatic environment. Of the approximately 23000 chemicals registered in the database of the National Swedish Product Register, 160 potential organic micropollutants were prioritized through quantitative knowledge of market availability, quantity used, extent of use on the market, and predicted compartment-specific environmental exposure during usage. Advanced liquid chromatography (LC)-HRMS-based suspect screening strategies were used to search for the selected compounds in 24 h composite samples collected from the effluent of three major wastewater treatment plants (WWTPs) in Sweden. In total, 36 tentative identifications were successfully achieved, mostly for substances not previously considered by environmental scientists. Of these substances, 23 were further confirmed with reference standards, showing the efficiency of combining a systematic prioritization strategy based on a regulatory database and a suspect-screening approach. These findings show that close collaboration between scientists and regulatory authorities is a promising way forward for enhancing identification rates of emerging pollutants and expanding knowledge on the occurrence of potentially hazardous substances in the environment.

Metabolic Pathway Extension Approach for Metabolomic Biomarker Identification

Discovery of metabolomic biomarkers represents an important task in disease diagnosis and therapy. Although the development of various analytical tools and online libraries facilitates the identification of biomarkers, the fast and reliable identification of new biomarkers that are not included in databases still represents a major bottleneck in the field of metabolomics. Here, we developed a metabolic pathway extension (MPE) approach to the fast characterization of metabolomic biomarkers. This approach was proposed based on a core concept that the whole metabolome is built from a limited number of initial metabolites via various kinds and multiple steps of metabolic reactions, and thus, theoretically, the whole metabolome might be mapped from the initial metabolites and metabolic reactions. Carnitine was used as an example of initial metabolites to validate this concept and the usefulness of MPE approach. The intragastric dosing of carnitine to mice induced a significant alternation of a total of 97 metabolites. Mass differences between each pair of metabolites were calculated and then matched with those of typical metabolic pathways automatically by an in-house developed program. Diagnostic ions and neutral losses were used for validating the matches. With this approach, 93 out of a total of 97 metabolites were putatively identified, while only half of them could be traced from the currently available online database. The MPE approach was further validated by applying to the identification of carnitine-associated biomarkers in a typical mice model of fasting, and extended to the development of bile acids submetabolome. Our study indicates that the MPE approach is highly useful for rapid and reliable identification of metabolically and structurally associated biomarkers.