Degradation studies of dimethachlor in soils and water by UHPLC-HRMS: putative elucidation of unknown metabolites

Degradation studies of dimethachlor in soils and water by UHPLC-HRMS: putative elucidation of unknown metabolites

February 2020.

López-Ruiz R; Romero-González R; Ortega-Carrasco E; Martínez Vidal JL; Garrido Frenich A

Abstract

Background

The analytical control of the presence of dimethachlor and its metabolites in environmental samples, such as water and soils, is a main concern. Degradation of this pesticide has been evaluated in two types of soils and two different water conditions at two concentration levels. For that purpose, a new liquid chromatography-mass spectrometry method has been developed and putative identification of new metabolites has been performed. 

Results

An analytical method based on ultra-high-performance liquid chromatography coupled to Orbitrap mass spectrometry (UHPLC-Orbitrap-MS) was developed to monitor the degradation of dimethachlor in environmental samples (water and soils). The degradation of dimethachlor in soils and groundwater samples has been monitored from 1 to 110 days after application of a plant protection product at two doses. Concentration of the parent compound slowly decreased in both matrices. 

DT50 values ranged from 40 to 70 days. Some metabolites were detected in the commercial product and in the samples one day after the application of the plant protection product. In addition, three new metabolites were putatively identified during dimethachlor degradation by untargeted analysis. 

Conclusions

In this study, the degradation of dimethachlor into its metabolites has been studied in soils and water, using a UHPLC-Orbitrap-MS validated method. A putative elucidation of new metabolites of dimethachlor has been carried out applying HRMS and software tools. Degradation results allowed for understanding the behavior of dimethachlor in soils and water and provided information regarding the possible risk of this pesticide and its metabolites to the ecosystem. 

LipostarMSI: Comprehensive, Vendor-Neutral Software for Visualization, Data Analysis, and Automated Molecular Identification in Mass Spectrometry Imaging

LipostarMSI: Comprehensive, Vendor-Neutral Software for Visualization, Data Analysis, and Automated Molecular Identification in Mass Spectrometry Imaging

January 2020.

Tortorella S, Tiberi P, Bowman AP, Claes BSR, Ščupáková K, Heeren RMA, Ellis SR, Cruciani G. 

Abstract

Mass spectrometry imaging (MSI) visualizes molecular distributions throughout tissues but is blind to dynamic metabolic processes. Here, MSI with high mass resolution together with multiple stable isotope labelling provided spatial analyses of phosphatidylcholine (PC) metabolism in mouse lungs. 

Dysregulated surfactant metabolism is central to many respiratory diseases. Metabolism and turnover of therapeutic pulmonary surfactants were imaged from distributions of intact and metabolic products of an added tracer, universally 13C-labelled dipalmitoyl PC (U13C-DPPC). The parenchymal 

distributions of newly synthesized PC species were also imaged from incorporations of methyl-D9- choline. This dual labelling strategy demonstrated both lack of inhibition of endogenous PC synthesis by exogenous surfactant and location of acyl chain remodeling processes acting on the U13C-DPPClabelled surfactant, leading to formation of polyunsaturated PC lipids. This ability to visualize discrete metabolic events will greatly enhance our understanding of lipid metabolism in diverse tissues and has potential application to both clinical and experimental studies. 

Mass spectrometry imaging of phosphatidylcholine metabolism in lungs administered with therapeutic surfactants and isotopic tracers

Mass spectrometry imaging of phosphatidylcholine metabolism in lungs administered with therapeutic surfactants and isotopic tracers

January 2021.

Shane R. Ellis, Emily Hall, Madhuriben Panchal, Bryn Flinders, Jens Madsen, Grielof KosterRon.M.AHeeren, Howard W. Clark, Anthony D. Postle 

Abstract

Mass spectrometry imaging (MSI) visualizes molecular distributions throughout tissues but is blind to dynamic metabolic processes. Here, MSI with high mass resolution together with multiple stable isotope labelling provided spatial analyses of phosphatidylcholine (PC) metabolism in mouse lungs. 

Dysregulated surfactant metabolism is central to many respiratory diseases. Metabolism and turnover of therapeutic pulmonary surfactants were imaged from distributions of intact and metabolic products of an added tracer, universally 13C-labelled dipalmitoyl PC (U13C-DPPC). The parenchymal 

distributions of newly synthesized PC species were also imaged from incorporations of methyl-D9- choline. This dual labelling strategy demonstrated both lack of inhibition of endogenous PC synthesis by exogenous surfactant and location of acyl chain remodeling processes acting on the U13C-DPPClabelled surfactant, leading to formation of polyunsaturated PC lipids. This ability to visualize discrete metabolic events will greatly enhance our understanding of lipid metabolism in diverse tissues and has potential application to both clinical and experimental studies. 

Use of lipidomics to investigate sebum dysfunction in juvenile acne

Use of lipidomics to investigate sebum dysfunction in juvenile acne

June 2016

Camera E, Ludovici M, Tortorella S, Sinagra JL, Capitanio B, Goracci L, Picardo M.

Abstract

Acne is a multifactorial skin disorder frequently observed during adolescence with different grades of severity. Multiple factors centering on sebum secretion are implicated in acne pathogenesis. Despite the recognized role of sebum, its compositional complexity and limited analytical approaches have hampered investigation of alterations specifically associated with acne. To examine the profiles of lipids distribution in acne sebum, 61 adolescents (29 males and 32 females) were enrolled in this study. Seventeen subjects presented no apparent clinical signs of acne. The 44 affected individuals were clinically classified as mild (13), moderate (19), and severe (12) acne. Sebum was sampled from the forehead with SebutapeTM adhesive patches. Profiles of neutral lipids were acquired with RR-RP/HPLC-TOF/MS in positive ion mode.  

Univariate and multivariate statistical analyses led to the identification of lipid species with significantly different levels between healthy and acne sebum. The majority of differentiating lipid species were diacylglycerols, followed by fatty acyls, sterols, and prenols. Overall, the data indicated an association between the clinical grading of acne and sebaceous lipid fingerprints and highlighted diacylglycerols as more abundant in sebum from adolescents affected with acne. 

Lipostar, a Comprehensive Platform-Neutral Cheminformatics Tool for Lipidomics

Lipostar, a Comprehensive Platform-Neutral Cheminformatics Tool for Lipidomics

May 2017.

Goracci L, Tortorella S, Tiberi P, Pellegrino RM, Di Veroli A, Valeri A, Cruciani G.

Abstract

To date, the main limitations for LC-MS-based untargeted lipidomics reside in the lack of adequate computational and cheminformatics tools that are able to support the analysis of several thousands of species from biological samples, enabling data mining and automating lipid identification and external prediction processes. To address these issues, we developed Lipostar, a novel vendor-neutral high-throughput software that effectively supports both targeted and untargeted LC-MS lipidomics, implementing data acquisition, user-friendly multivariate analysis (to be used for model generation and new sample predictions), and advanced lipid identification protocols that can work with or without the support of preformed lipid databases. Moreover, Lipostar integrates the lipidomic processes with a full metabolite identification (MetID) procedure, essential in drug safety applications and in translational studies. Case studies demonstrating a number of Lipostar features are also presented.