Tag Archives: 2018

Automatic MS Data Analysis to reveal the metabolic pathways of pesticides in fruits and soils

256th ACS National Meeting, Boston, MA (United States of America) 21 August, 2018 

Abstract

In the intensive farming of fruit and vegetable, a variety of pesticides are applied to prevent or eliminate harmful pests from plants. These pesticides can remain in edible parts as residues entering into the food chain. In most of the cases, pesticides can be transformed into metabolites, which are intermediate products of metabolism formed either in plants or animals. The detection of those metabolites does not end in the edible parts of the fruits and vegetables. It is also needed a deep study of soils and water to ensure that the concentration of harmful compounds will not reach the limit stablished by law. Advances in analytical techniques with increased sensitivity have led to the detection of a growing number of metabolites at low concentrations, being HPLC-HRMS the most used analytical method to perform this task. To boost the structure elucidation of the different metabolites, we used MassChemSite 2.0. 

Delving into the Polar Lipidome by Optimized Chromatographic Separation, High-Resolution Mass Spectrometry, and Comprehensive Identification with Lipostar: Microalgae as Case Study

October 2018.

 La Barbera G, Antonelli M, Cavaliere C, Cruciani G, Goracci L, Montone CM, Piovesana S, Laganà A, Capriotti AL

Abstract

The work describes the chromatographic separation optimization of polar lipids on Kinetex-EVO, particularly focusing on sulfolipids in spirulina microalgae (Arthrospira platensis). Gradient shape and mobile phase modifiers (pH and buffer) were tested on lipid standards. Different conditions were evaluated and resolution, peak capacity and peak shape calculated both in negative mode, for sulfolipids and phospholipids, and in positive mode, for glycolipids. A high confidence lipid identification strategy was also applied. In collaboration with software creators and developers, Lipostar was implemented to improve the identification of phosphoglycerolipids and to allow the  identification of glycosylmonoradyl and glycosyldiradyl-glycerols classes, the last being the main focus of this work. By this approach, an untargeted screening also for searching lipids not yet reported in the literature could be accomplished. The optimized chromatographic conditions and database search were tested for lipid identification first on the standard mixture, then on the polar lipid extract of spirulina microalgae, for which 205 lipids were identified. 

Structural elucidation tools to enhance organic synthesis productivity

66th ASMS Conference on Mass Spectrometry and Allied Topics, San Diego (United States of America) … 06 June 2018 

Abstract

The majority of organic synthesis workflows end up with the synthesis of at least few milligrams of pure compound, which structure is corroborated by Nuclear Magnetic Resonance spectroscopy.  Therefore, it needs first to use relatively large quantities of initial materials and purify the reaction crude before knowing if the desired compound has been obtained. The chemist uses LCMS prior purification to identify if a peak with the expected mass was formed. Nowadays there are Mass Spectrometry techniques that with the aid of computational algorithms can determine if the desired compound was obtained, as well as if there were other interesting compounds formed with minimal amount of sample and without the need of purification, making the synthetic process more time/cost effective. 

Peptide catabolite identification using HDMSE data and MassMetaSite processing

66th ASMS Conference on Mass Spectrometry and Allied Topics, San Diego (United States of America) … 06 June 2018 

Abstract

The study of peptide metabolism is needed to understand the structural elements that contribute to their clearance. Most of the MS techniques available today in peptide Metabolite Identification are based on DDA methods, often with a pre-defined list of ions. This methodology has the limitation that good quality MS 2 spectra are obtained for known metabolites, but possibility missing the unknown ones. Moreover, when the number of possible metabolites is high the preferred list would be too large to be effectively used. DIA methods have less potential to miss metabolites but do not have formally quad-resolved product ion spectra. In this study we report the comparison of DDA and DIA methods – MS Eand ion mobility-MS method (HDMS E) using Mass-MetaSite/WebMetabase processing.

From Experiments to a Fast Easy-to-Use Computational Methodology to Predict Human Aldehyde Oxidase Selectivity and Metabolic Reactions

January 2018.

Cruciani G, Milani N, Benedetti P, Lepri S, Cesarini L, Baroni M, Spyrakis F, Tortorella S, Mosconi E, Goracci L.

Abstract