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

Colloidal gold immunochromatographic assay for the detection of total aflatoxins in cereals

Aflatoxins (AFTs) are highly carcinogenic and mainly contaminate cereals. In this study, we designed and screened a hapten by analyzing the same characteristic groups of AFTs (AFB1, AFB2, AFG1 and AFG2), prepared a monoclonal antibody (mAb) 4C11 with a high sensitivity and specificity that can simultaneously detect all the main AFTs, and established a colloidal gold immunochromatographic assay (CG-ICA) for the detection of AFTs in cereals. The limits of detection (LODs) were 0.77 μg/kg, 1.40 μg/kg and 0.71 μg/kg for wheat, rice and maize, respectively, with linear ranges of 1.17-5.52 μg/kg, 1.84-5.20 μg/kg and 1.26-8.95 μg/kg, respectively. The spiked recoveries of AFTs samples ranged from 95.6 % to 104.2 %, and the positive samples further validated the reliability of the method. The results demonstrated that the method can be used for rapid, sensitive and efficient on-site detection of AFTs in cereals.

A stable and reusable aluminum-based metal-organic framework for the effective extraction of four aflatoxins from vegetable oils

The high specific surface area of metal-organic framework (MOF) materials endows them with efficient adsorption capabilities, thereby facilitating sample purification. In this study, a novel aluminum-based MOF (Al-MOF) was synthesized and employed as a solid-phase extraction (SPE) adsorbent for the purification of aflatoxins B1 (AFB1), AFB2, AFG1, and AFG2 in vegetable oils. It was revealed that Al-MOF adsorbs aflatoxins through hydrogen bonding and π-π interactions. Under optimal SPE conditions, liquid chromatography-tandem mass spectrometry analysis yielded limits of detection ranging from 0.06 to 0.25 μg/kg and limits of quantification from 0.21 to 0.84 μg/kg for the four aflatoxins. Recovery rates at concentrations of 5, 10, and 20 μg/kg ranged from 74 % to 110 %, with coefficients of variation below 11 %. This method achieves efficient and cost-effective purification of aflatoxins in vegetable oils. Compared to national standard methods, this approach offers advantages such as lower material costs, ease of storage, and reusability.

Electrochemiluminescence and fluorescence dual-mode monitoring of aflatoxin B1 production based on single Ru-MOF particles and FITC luminophores

Herein, an electrochemiluminescence (ECL) and fluorescence (FL) dual-mode imaging biosensing platform was developed for onsite and dynamic monitoring of aflatoxin B1 (AFB1) production in the corn molding process. Zinc metal organic framework structures encapsulated with Ru(bpy)32+ (Ru-MOF) were employed as ECL signal probes for single particle imaging with stable luminescent intensity and high emission efficiency. Fluorescein Isothiocyanate (FITC) luminophores, served as fluorescent probes, were conjugated with AFB1 aptamer modified on the electrode surface, which enabled the observation of green luminescent spots in FL mode. When exposed to target AFB1, FITC luminophores detached from the surface of electrode, leading to a notable decrease in the number of green luminescent spots. Single Ru-MOF particles were then immobilized onto the surface of electrode through DNA coupling and discernible luminescent spots could be watched in ECL mode. Under optimal circumstances, a dual-mode imaging platform was constructed for AFB1 determination with a linear relationship of 1.0 fg/mL to 1.0 pg/mL in both ECL and FL mode. The detection limit (LOD) was 0.89 fg/mL in FL mode and 0.84 fg/mL in ECL mode, which demonstrated superior sensitivity. The imaging biosensor was established for dynamic tracking of AFB1 production in corn molding process. The results showed that aflatoxin production occurred more rapidly at damaged areas of the corn compared to areas with intact surfaces. The intact corn got moldy on the third day and its surface AFB1 concentration was calculated as 14.16 fg/mL. Combining the ECL and FL imaging technology with dual-mode biosensing, this work achieves high sensitivity, accuracy and capability of dynamic monitoring for AFB1 sensing which provides innovative ideas for the rational design of aflatoxin sensors, and holds substantial promise in food safety.

TG-MS Analysis for Elemental Composition of Organic Matters and Their Structural Properties

A novel approach for determining the elemental content of organic matter through thermal gravimetric analysis coupled online with a mass spectrometer (TG-MS) is disclosed. This method not only yields results equivalent to ASTM analysis but also provides insight into the covalent bond structure within the sample. The principle of this technique consists of the combustion of organic matter in an oxygen-enriched environment within the thermogravimetric (TG) system. The gases generated during combustion, including carbon-containing gases such as CO2 and CO, hydrogen-containing gases such as H2O, nitrogen-containing gases such as NO2 and NO, and sulfur-containing gases such as SO2, are then analyzed using online MS. Quantitative analysis of these gases is accomplished via an external standard method, facilitating the determination of the elemental content of the organic matters. The experiment employed a temperature-programmed heating rate of 10 °C/min, a carrier gas flow rate of 100 mL/min, and an oxygen concentration of 50% by volume. We conducted tests on a range of 23 samples, including coal, heavy oil, oil shale, and biomass. The results for coal, oil shale, and biomass samples were consistent with ASTM standards, while the heavy oil samples demonstrated slightly lower values compared with ASTM methods. Furthermore, we probed into the mass loss and gas generation processes that occur during the combustion of samples, and these results enhance the understanding of the mechanism of organic matter combustion as well as that of the covalent bond structure of organic matters.

Fast neonicotinoid quantification in honey using the one-point internal calibration approach

Neonicotinoids, a highly effective class of insecticides used worldwide, have been identified as a major cause of concern for biodiversity. To assess the ecological and environmental consequences of neonicotinoids' use, reliable analytical methodologies, including calibration approaches, are needed. Here, we compared the performance of internal calibration (IC) using a single concentration of stable isotope-labeled standard (SIL) with classical multipoint external calibration (EC) for the quantification of six neonicotinoids in honey. IC showed acceptable levels of trueness (86.3% - 116.0%) and precision (1.4% - 20.8%), although slight biases were observed at very low concentrations compared to EC. When applied to 32 original honey samples, both approaches showed strong agreement (R2 > 0.998) with proportional biases lower than 5%. These results highlight the possibility of implementing IC to simplify quantification in liquid chromatography-mass spectrometry-based pesticide applications.

Application of Biosensors and Biomimetic Sensors in Dairy Products Testing

This article summarizes the applications of biosensors and biomimetic sensors in the detection of residues in dairy products. Biosensors utilize biological molecules such as enzymes or antibodies to detect residual substances in dairy products, demonstrating high specificity and sensitivity. Biomimetic sensors, inspired by biosensors, use synthetic materials to mimic biological sensing mechanisms, enhancing stability and reproducibility. Both sensor types have achieved significant success in detecting pesticide residues, veterinary drugs, bacteria, and other contaminants in dairy products. The applications of biological and biomimetic sensors not only improve the efficiency of residue detection in dairy products but also have the potential to reduce the time and cost of traditional methods. Their specificity and high sensitivity make them powerful tools in the dairy industry, thus contributing to ensuring the quality and safety of dairy products and meeting the growing consumer demands for health and food safety.

Advancing High-Throughput MS-Based Protein Quantification: A Case Study on Quantifying 10 Major Food Allergens by LC-MS/MS Using a One-Sample Multipoint External Calibration Curve

The LC-MS-based method has emerged as the preferred approach for quantifying food allergens. However, the preparation of a traditional calibration curve (MSCC) is labor-intensive and error-prone. Here, a sensitive and robust LC-MS/MS method for quantifying 10 major food allergens was developed and validated, where the one-sample multipoint external calibration curve (OSCC) was employed instead of MSCC. By employing the multiple isotopologue reaction monitoring (MIRM) technique with only one spiked level in the blank, OSCC can be effectively established. Results demonstrate that the proposed method exhibits excellent performance in selectivity, sensitivity, accuracy, and precision, comparable to that of the traditional MSCC. Additionally, this strategy allows for isotope sample dilution by monitoring the less abundant MIRM channel. Moreover, the developed method was successfully applied to investigate the contamination of 10 food allergens in commercial food products. With its high throughput and robustness, the MIRM-OSCC-LC-MS/MS methodology has many potential applications, especially in the MS-based protein quantification analysis.

Integrating a Multiple Isotopologue Reaction-Monitoring Technique and LC-MS/MS for Quantitation of Small Molecules: Ten Mycotoxins in Cereals as an Example

Accurate quantification of mycotoxin in cereals is crucial for ensuring food safety and human health. However, the preparation of traditional multisample external calibration curves (MSCCs) is labor-intensive and error-prone. Here, a multiple isotopologue reaction-monitoring (MIRM)-LC-MS/MS method for accurate quantitation of ten major mycotoxins in cereals was successfully developed and validated, where a novel one-sample multipoint calibration curve (OSCC) strategy is used instead of MSCCs. The OSCC can be established by examining the correlation between the calculated theoretical isotopic abundances and the measured abundance across various MIRM channels. In comparison to the MSCC, the OSCC strategy exhibits outstanding performance including superior selectivity, accuracy (78.4-108.6%), and precision (<12.5%). Furthermore, the proposed OSCC-MIRM-LC-MS/MS method was successfully applied to investigate mycotoxin contamination in cereal samples in China. Considering the advantages of simplified workflows and improved throughput, the OSCC-MIRM-LC-MS/MS methodology holds great promise for accurately quantifying chemical contaminants in foods.

Quantitative Analytical and Computational Workflow for Large-Scale Targeted Plasma Metabolomics

Quantifying metabolites from various biological samples is necessary for the clinical and biomedical translation of metabolomics research. One of the ongoing challenges in biomedical metabolomics studies is the large-scale quantification of targeted metabolites, mainly due to the complexity of biological sample matrices. Furthermore, in LC-MS analysis, the response of compounds is influenced by their physicochemical properties, chromatographic conditions, eluent composition, sample preparation, type of MS ionization source, and analyzer used. To facilitate large-scale metabolite quantification, we evaluated the relative response factor (RRF) approach combined with an integrated analytical and computational workflow. This approach considers a compound's individual response in LC-MS analysis relative to that of a non-endogenous reference compound to correct matrix effects. We created a quantitative LC-MS library using the Skyline/Panorama web platform for data processing and public sharing of data. In this study, we developed and validated a metabolomics method for over 280 standard metabolites and quantified over 90 metabolites. The RRF quantification was validated and compared with conventional external calibration approaches as well as literature reports. The Skyline software environment was adapted for processing such metabolomics data, and the results are shared as a "quantitative chromatogram library" with the Panorama web application. This new workflow was found to be suitable for large-scale quantification of metabolites in human plasma samples. In conclusion, we report a novel quantitative chromatogram library with a targeted data analysis workflow for biomedical metabolomic applications.