Novel one-point calibration strategy for high-throughput quantitation of microcystins in freshwater using LC-MS/MS

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.

Self-assembly flexible SERS imprinted membrane based on Ag nanocubes for selective detection of microcystin-LR

Silver nanocubes monolayer-modified polydimethylsiloxane (Ag NC/PDMS) flexible SERS substrates have been prepared by a three-phase interface self-assembly procedure. The combination of this method with membrane technology brings nanoparticles in close proximity, densely, and regularly arranged in monolayers over a large area, leading to excellent SERS properties. Considering the complexity of practical detection, molecular imprinted polymers (MIPs) were anchored on the surface of SERS substrate and applied to selective detection of microcystin-LR (MC-LR). It is worth mentioning that the SERS imprinted membranes (AP-MIMs) were still clearly detected at a concentration of 0.1 µg·L-1 of MC-LR in drinking water, and the detection limit was as low as 0.0067 µg·L-1. The substrate exhibited excellent uniformity with a relative standard deviation (RSD) of 6.1%. In the presence of interference molecules, AP-MIMs exhibited excellent selectivity for MC-LR. Furthermore, in the spiking and recovery tests of practical lake water samples, the method showed excellent recoveries ranging from 96.47 to 105.31%. It has been demonstrated that the prepared AP-MIMs can be applied to sensitive and specific detection of trace amounts of MC-LR in drinking water.

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.

Freshwater Cyanobacterial Toxins, Cyanopeptides and Neurodegenerative Diseases

Cyanobacteria produce a wide range of structurally diverse cyanotoxins and bioactive cyanopeptides in freshwater, marine, and terrestrial ecosystems. The health significance of these metabolites, which include genotoxic- and neurotoxic agents, is confirmed by continued associations between the occurrence of animal and human acute toxic events and, in the long term, by associations between cyanobacteria and neurodegenerative diseases. Major mechanisms related to the neurotoxicity of cyanobacteria compounds include (1) blocking of key proteins and channels; (2) inhibition of essential enzymes in mammalian cells such as protein phosphatases and phosphoprotein phosphatases as well as new molecular targets such as toll-like receptors 4 and 8. One of the widely discussed implicated mechanisms includes a misincorporation of cyanobacterial non-proteogenic amino acids. Recent research provides evidence that non-proteinogenic amino acid BMAA produced by cyanobacteria have multiple effects on translation process and bypasses the proof-reading ability of the aminoacyl-tRNA-synthetase. Aberrant proteins generated by non-canonical translation may be a factor in neuronal death and neurodegeneration. We hypothesize that the production of cyanopeptides and non-canonical amino acids is a more general mechanism, leading to mistranslation, affecting protein homeostasis, and targeting mitochondria in eukaryotic cells. It can be evolutionarily ancient and initially developed to control phytoplankton communities during algal blooms. Outcompeting gut symbiotic microorganisms may lead to dysbiosis, increased gut permeability, a shift in blood-brain-barrier functionality, and eventually, mitochondrial dysfunction in high-energy demanding neurons. A better understanding of the interaction between cyanopeptides metabolism and the nervous system will be crucial to target or to prevent neurodegenerative diseases.