An untargeted analytical workflow based on Kendrick mass defect filtering reveals dysregulations in acylcarnitines in prostate cancer tissue.

BACKGROUND: Metabolomics is nowadays considered one the most powerful analytical for the discovery of metabolic dysregulations associated with the insurgence of cancer, given the reprogramming of the cell metabolism to meet the bioenergetic and biosynthetic demands of the malignant cell. Notwithstanding, several challenges still exist regarding quality control, method standardization, data processing, and compound identification. Therefore, there is a need for effective and straightforward approaches for the untargeted analysis of structurally related classes of compounds, such as acylcarnitines, that have been widely investigated in prostate cancer research for their role in energy metabolism and transport and ß-oxidation of fatty acids. RESULTS: In the present study, an innovative analytical platform was developed for the straightforward albeit comprehensive characterization of acylcarnitines based on high-resolution mass spectrometry, Kendrick mass defect filtering, and confirmation by prediction of their retention time in reversed-phase chromatography. In particular, a customized data processing workflow was set up on Compound Discoverer software to enable the Kendrick mass defect filtering, which allowed filtering out more than 90 % of the initial features resulting from the processing of 25 tumoral and adjacent non-malignant prostate tissues collected from patients undergoing radical prostatectomy. Later, a partial least square-discriminant analysis model validated by repeated double cross-validation was built on the dataset of 74 annotated acylcarnitines, with classification rates higher than 93 % for both groups, and univariate statistical analysis helped elucidate the individual role of the annotated metabolites. SIGNIFICANCE: Hydroxylation of short- and medium-chain minor acylcarnitines appeared to be a significant variable in describing tissue differences, suggesting the hypothesis that the neoplastic growth is linked to oxidation phenomena on selected metabolites and reinforcing the need for effective methods for the annotation of minor metabolites.

Preparation of Monolith for Online Extraction and LC-MS Analysis of ß-Estradiol in Serum Via a Simple Multicomponent Reaction.

Multicomponent reactions offer efficient and environmentally friendly strategies for preparing monoliths suitable for applications in analytical chemistry. In the described study, a multicomponent reaction was utilized for the one-pot miniaturized preparation of a poly(propargyl amine) polymer inside commercial silica-lined PEEK tubing. The reaction involved only small amounts of reagents and was characterized by atom economy. The resulting monolithic column was incorporated into an autosampler system for the online extraction and cleanup of ß-estradiol from human serum. Sample pretreatment was simplified to a simple dilution with methanol and centrifugation to remove proteins. The resulting platform included LC-MS analysis in multiple reaction monitoring for quantitative analysis of ß-estradiol. The method was validated in serum, demonstrating practical applicability for the monitoring of fertile women. Recoveries were above 94%, and LOD and LOQ values at 0.008 and 0.18 ng mL-1, respectively. The developed platform proved to be competitive with previous methods for solid-phase microextraction of ß-estradiol in serum, with comparable recovery and sensitivity but with the advantage of nearly complete automation. The environmental impact of the process was evaluated as acceptable due to the miniaturization of the monolith synthesis and the automation of extraction. The drawback associated with the LC-MS technique can be reduced by the inclusion of additional analytes in a single investigation. The work demonstrates that multicomponent reactions are versatile, economical, and possibly a green methodology for producing reversed-phase and mixed-mode sorbents, enabling miniaturization of the entire analytical procedure from the preparation of extraction sorbents to analysis.

One-phase extraction coupled with photochemical reaction allows the in-depth lipid characterization of hempseeds by untargeted lipidomics.

Due to their valuable nutritional content, several hemp-derived products from hempseeds have recently been placed in the market as food and food ingredients. In particular, the lipid composition of hempseeds has raised interest for their rich content in biologically active polyunsaturated fatty acids with an optimum ratio of omega-3 and omega-6 compounds. At present, however, the overall polar lipidome composition of hempseeds remains largely unknown. In the present work, an analytical platform was developed for the extraction, untargeted HRMS-based analysis, and detailed annotation of the lipid species. First, five one- and two-phase solid-liquid extraction protocols were tested and compared on a hempseed pool sample to select the method that allowed the overall highest efficiency as well as easy coupling with lipid derivatization by photochemical [2 + 2] cycloaddition with 6-azauracil. Underivatized lipids were annotated employing a data processing workflow on Compound Discoverer software that was specifically designed for polar lipidomics, whereas inspection of the MS/MS spectra of the derivatized lipids following the aza-Paternò-Büchi reaction allowed pinpointing the regiochemistry of carbon-carbon double bonds. A total of 184 lipids were annotated, i.e., 26 fatty acids and 158 phospholipids, including minor subclasses such as N-acylphosphatidylethanolamines. Once the platform was set up, the lipid extracts from nine hempseed samples from different hemp strains were characterized, with information on the regiochemistry of free and conjugated fatty acids. The overall analytical approach helped to fill a gap in the knowledge of the nutritional composition of hempseeds.

Untargeted Analysis of Short-Chain Peptides in Urine Samples Short Peptides Analysis.

Short-chain peptides have attracted increasing attention in different research fields, including biomarker discovery, but also a well-known analytical challenge in complex matrices due to their low abundance compared to other molecules, which can cause extensive ion suppression during mass spectrometric acquisition. Moreover, there is a lack of analytical workflows for their comprehensive characterization since ordinary peptidomics strategies cannot identify them. In this context, an enrichment strategy was introduced and developed to isolate and clean up short-chain peptides by graphitized carbon black solid phase extraction. For better coverage of peptide polarity, urine samples were analyzed by ultrahigh performance liquid chromatography by reversed-phase and hydrophilic interaction liquid chromatography. High-resolution mass spectrometry allowed the detection of the eluting peptides by data-dependent mode using a suspect screening strategy with an inclusion list; peptides were identified by a semiautomated workflow implemented on Compound Discoverer. The complementarity of the orthogonal separation strategy was confirmed by peptide identification, resulting in 101 peptides identified from the RP runs, and 111 peptides from the HILIC runs, with 60 common identifications.

Dispersive solid phase extraction using a hydrophilic molecularly imprinted polymer for the selective extraction of patulin in apple juice samples.

A molecularly imprinted polymer with a specific selectivity for patulin was successfully synthesized. The molecularly imprinted material was prepared using the two functional monomers dopamine and melamine and formaldehyde as the cross-linker. The resulting material possessed a large number of hydrophilic groups, such as hydroxyls, imino groups, and ether linkages. For the first time, uric acid was used as a dummy template for its structural similarity to patulin. Comprehensive characterization and detailed studies of the adsorption process were carried out via adsorption isotherms, while the rate-limiting steps were investigated using adsorption kinetics. Separation, determination, and quantification of patulin were achieved by ultra-high performance liquid chromatography coupled with both photodiode array detection and tandem mass spectrometry. The latter was applied to patulin confirmation in the analysis of real samples. The methodology was validated in 20 apple juice samples. The results showed that the developed hydrophilic molecularly imprinted polymer had high selectivity and specific adsorption towards patulin, with mean recoveries ranging between 85 and 90% and a relative standard deviation lower than 15%. The developed molecularly imprinted polymer exhibited good linearity in the range 1-100 ng mL-1 with coefficient of determination (R2) > 0.99. The limit of detection was 0.5 ng mL-1, and the limit of quantification was 1 ng g-1. The developed method showed a good purification capacity for apple juices due to its hydrophilic nature and the polar interactions established with the target analyte.

Occurrence of per- and polyfluorinated alkyl substances in wastewater treatment plants in Northern Italy.

Wastewater treatment plants are known to be relevant input sources of per- and polyfluoroalkyl substances (PFAS) in the aquatic environment. This study aimed to investigate the occurrence, fate, and seasonal variability of twenty-five PFAS in four municipal wastewater treatment plants (WWTP A, B, C, and D) surrounding the city of Milan (Northern, Italy). Composite 24-h wastewater samples were collected in July and October 2021 and May and February 2022 from influents and effluents of the four WWTPs. PFAS were detected at concentrations ranging between 24.1 and 66.9 µg L-1 for influent and 13.4 and 107 µg L-1 for effluent wastewater samples. Perfluoropentanoic acid was the most abundant (1.91-30.0 µg L-1) in influent samples, whereas perfluorobutane sulfonic acid predominated (0.80-66.1 µg L-1) in effluent samples. In sludge, PFOA was detected in plant A at concentrations in the range of 96.6-165 ng kg-1 dw in primary sludge samples and 98.6-440 ng kg-1 dw in secondary treatment sludge samples. The removal efficiency of total PFAS varied between 6 % and 96 %. However, an increase of PFAS concentrations was observed from influents to effluents for plant D (during July and October), plant A (during October and May), and plant C (during May) indicating that biotransformation of PFAS precursors can occur during biological treatments. This was supported by the observed increase in concentrations of PFOA from primary to secondary treatment sludge samples in plant A. Moreover, the plant operating at shorter hydraulic retention times (plant D) showed lower removal efficiency (<45 %). Seasonal variation of PFAS in influent and effluent appears rather low and more likely due to pulse release instead of seasonal factors.