Product ion isotopologue pattern: A tool to improve the reliability of elemental composition elucidations of unknown compounds in complex matrices

Critical Evaluation of Two Qualitative Analytical Approaches for Multiclass Determination of Veterinary Drugs in Bovine Muscle Using UHPLC-Q-Orbitrap: The Wind of Change in Brazilian Monitoring

Food safety is recognized as a main requirement for consumers, food industries, and official laboratories. Here, we present the optimization and screening qualitative validation of two multianalyte methods in bovine muscle tissues by ultra-high-performance liquid chromatography coupled to high-resolution mass spectrometry with an Orbitrap-type analyzer, operated with a heated ionization source in positive and negative mode. This aims for not only the simultaneous detection of veterinary drugs regulated in Brazil but also the prospection of antimicrobials not yet monitored. Two different sample preparation procedures were applied: method A-generic solid-liquid extraction with 0.1% formic acid (v/v) in an aqueous solution of EDTA 0.1% (w/v)-acetonitrile-methanol (1:1:1, v/v/v), followed by an additional ultrasound-assisted extraction and method B-QuEChERS. In both procedures, selectivity showed satisfactory conformity. From a detection capability (CCβ) equivalent to ½ the maximum residue limit, >34% of the analyte resulted in a false positive rate of <5%, preponderant by the QuEChERS method, which exhibited a higher yield of the sample. The results showed the potential application of both procedures in the routine analysis of foods by official laboratories, enabling the expansion of this methodological portfolio as well as its analytical scopes, thus optimizing the control of residues of veterinary drugs in the country.

Simplifying Nontargeted Analysis of PFAS in Complex Food Matrixes

Background

Per- and polyfluoroalkyl substances (PFAS) are a class of toxic environmental contaminants that are characterized by their high chemical stability and enormous structural diversity.

Objective

The limited availability of PFAS reference standards is the main motivation for developing nontargeted analytical methods. Current concepts are complex and rely on multiple filtering steps (e.g., assumption of homologous series, detection of mass defects, generic fragments, and spectra obtained from web-based sources).

Method

High-resolution mass spectrometry (HRMS)–based chromatograms of fish liver extracts were deconvoluted. Based on the ion abundance between the monoisotopic and the first isotopic peak, the number of carbons (C) was estimated for each extracted feature. A mass over carbon (m/C) and mass defect over carbon (md/C) ratio was calculated.

Results

PFAS-related peaks are strongly discriminated from matrix peaks when plotting m/C versus md/C. This enables nontarget detection of PFAS present at low µg/kg concentration in complex food matrixes.

Conclusions

The proposed concept is highly selective by revealing a relatively small number of high-probability PFAS candidates (features). The small number of surviving candidates permits the MS/MS-based confirmation of each feature. This strategy led to the finding of one PFAS not present in the reference standard solution, as well as the detection of an unexpected set of PFAS adducts.

Highlights

The proposed concept of mass over carbon versus mass defect over carbon is suited for the nontarget detection of low amounts of PFAS in complex matrixes. It should be capable of detecting any PFAS (F/H ratio should be &gt;1:1) regardless of the ionization mode.

Incurred Sample Reanalysis: Time to Change the Sample Size Calculation?

Reliable results of pharmacokinetic and toxicokinetic studies are vital for correct decision making during drug discovery and development. Thus, ensuring high quality of bioanalytical methods is of critical importance. Incurred sample reanalysis (ISR)-one of the tools used to validate a method-is included in the bioanalytical regulatory recommendations. The methodology of this test is well established, but the estimation of the sample size is still commented on and contested. We have applied the hypergeometric distribution to evaluate ISR test passing rates in different clinical study sizes. We have tested both fixed rates of the clinical samples-as currently recommended by FDA and EMA-and a fixed number of ISRs. Our study revealed that the passing rate using the current sample size calculation is related to the clinical study size. However, the passing rate is much less dependent on the clinical study size when a fixed number of ISRs is used. Thus, we suggest using a fixed number of ISRs, e.g., 30 samples, for all studies. We found the hypergeometric distribution to be an adequate model for the assessment of similarities in original and repeated data. This model may be further used to optimize the sample size needed for the ISR test as well as to bridge data from different methods. This paper provides a basis to re-consider current ISR recommendations and implement a more statistically rationalized and risk-controlled approach.

D2O Labeling to Measure Active Biosynthesis of Natural Products in Medicinal Plants

Plant natural products have served as a prominent source of medicines throughout human history, and are still used today as clinically-approved pharmaceuticals. However, many medicinal plants that produce useful compounds are slow-growing or recalcitrant to cultivation, making it difficult to investigate the underlying genetic/enzymatic machinery responsible for biosynthesis. To better understand the metabolism of bioactive natural products in slow-growing medicinal plants, we used D2O labeling and LC-MS-based metabolomics to explore the biosynthesis of medically-relevant alkaloids in three plant species. Our results provide evidence for sites of active biosynthesis for these alkaloids, and demonstrate that D2O labeling can be used as a general method to determine sites of active secondary metabolism over relatively short time scales. We anticipate that these results will facilitate discovery of complete metabolic pathways for plant natural products of medicinal importance, especially for approaches that rely upon transcriptomics and knowledge of active metabolism to identify biosynthetic enzymes.