Category Archives: Resource Library

HomeMass Analytica –  Resource Library

Rediscovering Halophyte Suaeda maritima as an Alternative crop for Food Lipids Through Aquaponic Cultivation and Lipidomics analysis

Rediscovering Halophyte Suaeda maritima as an Alternative crop for Food Lipids Through Aquaponic Cultivation and Lipidomics analysis

September 24, 2025

Marisa Pinho, Ana S. P. Moreira, Erika García Cardesín, Alexandra Pérez-González, David Gómez-Carnota, Bruna B. Neves, Stefano Bonciarelli, Laura Goracci, Tânia Melo, Pedro Domingues, Ana I. Lillebø, Javier Cremades, M. Rosário Domingues

Abstract

Halophytes are gaining recognition for their resilience and nutritional properties. Salicornia is widely consumed in Western countries. Other species like Suaeda genus have long-standing medicinal and culinary uses but remain underexplored. They can thrive in saline environments and aquaculture. Aquaponic cultivation, which can valorize aquaculture effluents and be integrated into IMTA-RAS systems, is a soil-free method that optimizes biomass and biochemical composition while reducing land and freshwater use. This study evaluated the benefits of aquaponically cultivating S. maritima, focusing on biomass yield and lipid composition. Lipidome profiling of aerial organs was conducted with LC-MS/MS and GC-MS. Biomass fresh weight increased significantly from 0.74 to 216 mg after 8-weeks of cultivation. Seventeen FA were identified, including essential FA18:2n-6 and FA18:3n-3, more abundant in aquaponic samples. Lipidomic analysis revealed 448 lipid species, including glycerophospholipids, glycolipids, acylglycerols, sphingolipids, sterol lipids, and prenol lipids. Aquaponic samples exhibited higher levels of PUFA-rich glycolipids, associated with anti-inflammatory properties, and wild samples containing more sphingolipids and acylglycerols. Glycerophospholipid profiles varied between 4- and 8-weeks. Aquaponic cultivated biomass have a more stable lipid composition than biomass collected from wild. These findings suggests aquaponic cultivation is a valuable technique for stable lipid composition, enhancing its potential as a sustainable food source.

Read the article

Lipidomics‐Guided Ultrasound‐Assisted Ethanol Extraction of Avocado Pulp and Evaluation of Bioactive Properties

Lipidomics‐Guided Ultrasound‐Assisted Ethanol Extraction of Avocado Pulp and Evaluation of Bioactive Properties

September 30, 2025

Bruna B. Neves, Rita Pais, Joana Batista, Marisa Pinho, Tatiana Maurício, Stefano Bonciarelli, Laura Goracci, Bruno Neves, Pedro Domingues, M. Rosário Domingues, Tânia Melo

Abstract

Avocados are a valuable source of lipids with potential applications in food, nutraceutical, and cosmetic products, all requiring food-grade and environmentally friendly extraction methods. Though often enjoyed fresh, avocado pulp is also processed for oil. However, conventional extraction techniques can compromise pulp lipid composition, triggering the need for alternative methods that preserve pulp lipid integrity and meet industrial sustainability standards. Ultrasound probe-assisted extraction using ethanol, a green solvent, could be a sustainable alternative to extract lipids from avocado pulp. In the present study, lipid profiles from Hass Portuguese avocado pulp were characterized using C18 reversed-phase HPLC-MS/MS, and their biological activities were evaluated. Folch-like extraction was employed as a benchmark for comparison. Untargeted lipidomics profiling revealed over 100 lipid species across polar and neutral classes, with triacylglycerides enriched in essential polyunsaturated fatty acids. Ultrasound-assisted ethanol extraction achieved ≈70% lipid purity and yielded a lipid composition comparable to that of the conventional method. Notably, green pulp extract exhibited significant bioactivity, including moderate antioxidant activity and powerful anti-inflammatory effects, inhibiting COX-2 and reducing nitric oxide levels at low concentrations. These findings support the use of ultrasound-assisted ethanol extraction as an efficient and sustainable strategy for obtaining bioactive compounds from avocado pulp, reinforcing its potential incorporation into high-value or even new formulations.

Read the article

The LambdaGap Framework for Precision-Oriented Ranking

The LambdaGap Framework for Precision-Oriented Ranking

June 16, 2025

Ramon Adàlia, Gemma Sanjuan, Tomàs Margalef, Ismael Zamora

Abstract

LambdaRank has proven effective for optimizing information retrieval metrics such as Normalized Discounted Cumulative Gain (NDCG). However, its application to Precision at document k (P@k) poses significant challenges because of the metric’s unique definition, which heavily restricts the number of effective training document pairs. This limitation diminishes the learning signal for relevant documents beyond the top k, potentially resulting in suboptimal performance. To overcome this, we propose LambdaGap, a ranking algorithm inspired by LambdaRank specifically tailored for optimizing P@k. LambdaGap replaces the pairwise weighting scheme in LambdaRank by one where pairs of documents within k positions in the ranking are masked out. We establish a theoretical link between LambdaGap and P@k by identifying the implicit metric optimized by the model. Furthermore, we introduce a new metric, Average Relevance Position beyond document k, which can be used in conjunction with LambdaRank to indirectly optimize for P@k. Our extensive experiments on publicly available datasets demonstrate the effectiveness of the proposed methods, yielding statistically significant improvements in P@k performance and highlighting their potential for more efficient training.

Read the article

An automated software-assisted approach for exploring metabolic susceptibility and degradation products in macromolecules using high-resolution mass spectrometry

An automated software-assisted approach for exploring metabolic susceptibility and degradation products in macromolecules using high-resolution mass spectrometry

August 13, 2025

Paula Cifuentes, Ismael Zamora, Tatiana Radchenko, Fabien Fontaine, Albert Garriga, Luca Morettoni, Jesper Kammersgaard Christensen, Hans Helleberg, Bridget A. Becker

Abstract

A comprehensive understanding of drug metabolism is crucial for advancements in drug development. Automation has improved various stages of this process, from compound procurement to data analysis, but significant challenges persist in the metabolite identification (MetID) of macromolecules due to their size, structural complexity, and associated computational demands. This study introduces new algorithms for automated Liquid Chromatography-High-Resolution Mass Spectrometry (LC-HRMS) data analysis applicable to macromolecules. A novel peak detection approach based on the most abundant mass (MaM) is presented and systematically compared with the monoisotopic mass (MiM) approach, commonly used in small molecules MetID. Additionally, three structure visualization strategies, expanded (atom-level), non-expanded (monomer-level), and a hybrid mode, are evaluated for their impact on computation data processing time and interpretability, based on their distinct fragmentation strategies. The workflow was validated using six diverse datasets, comprising linear and cyclic peptides and oligonucleotides with both natural and unnatural monomers, covering a molecular weight range of 700–7630 Da. A total of 970 metabolites were identified under various experimental and ionization conditions. The MaM algorithm demonstrated higher scores and a greater number of matches, instilling greater confidence in the accurate prediction of metabolite structures, while the non-expanded visualization significantly reduced processing times (ranging from minutes to under an hour for most peptides). Furthermore, the visualization algorithm, which integrates monomer-level and atom/bond notation, enables clear localization of metabolic biotransformations. Compared to previous studies, the proposed workflow demonstrated reduced processing time, consistent detection of degradation products, and enhanced visualization capabilities, advancing automated MetID for macromolecules.

Read the article

Bioorthogonal Click Chemistry in LC-MS lipidomics to trace lipid metabolism: from experimental data to high-throughput computational analysis

Bioorthogonal Click Chemistry in LC-MS lipidomics to trace lipid metabolism: from experimental data to high-throughput computational analysis

Metabolomics 2025. 22-26 June.

Stefano Bonciarelli1; Palina Nepachalovich2; Gabriele Lombardi Bendoula2; Jenny Desantis3; Michela Eleuteri3; Christoph Thiele4; Laura Goracci3; Maria Fedorova2

1Mass Analytica, Sant Cugat del Valles, Spain; 2Center of Membrane Biochemistry and Lipid Research, Faculty of Medicine Carl Gustav Carus, Technical University Dresden, Dresden, Germany; 3Department of Chemistry, Biology and Biotechnology, University of Perugia, Perugia, Italy; 4Life & Medical Sciences Institute, University of Bonn, Bonn, Germany

Abstract

Investigating lipid metabolism is crucial for understanding its role in health and disease. Recently, lipid metabolic tracing using bioorthogonal click chemistry has emerged as a powerful alternative to stable isotope tracers. [1,2] Thiele and colleagues showed that ω-alkyne-functionalized fatty acids, derivatized with azido-quaternary ammonium reporters, offer advantages like enhanced ionization and specific neutral loss, enabling high-throughput, sensitive lipid analysis. However, direct injection MS faces challenges, such as resolving isomeric species and possible occurrence of false positives from unaccounted in-source fragmentation. [3]

To address these limitations, we present an integrated LC-MS and bioinformatics platform for high-throughput lipid tracing using bioorthogonal click chemistry. [4] Synthetic standards and endogenously produced alkyne lipids were used to explore the LC-MS behavior of “clicked” lipid species with the C171 azido-quaternary ammonium reporter. Key factors like preferential adduct formation, in-source fragmentation (ISF), and MS/MS fragmentation patterns were annotated across 23 lipid subclasses. Fragmentation rules for each subclass were implemented in Lipostar2 software, enabling high-throughput annotation and quantification of 224,514 “clicked” lipids from 15 lipid classes.[4]

We validated the platform by tracing palmitic and oleic acids in HT1080 fibrosarcoma cells under fatty acid overload. High-throughput analysis identified 479 “clicked” lipids in palmitic acid-treated cells and 379 in oleic acid-treated cells, with species labeled singly, doubly, or triply. Distinct incorporation patterns were observed, including isomeric sphingolipid species, where the tracer incorporated into either the fatty acyl or sphingoid base. LC-MS revealed ISF products that would be indistinguishable from endogenous lipids by other methods. [4]

In conclusion, this integrated platform enables efficient, high-throughput analysis of “clicked” lipid tracers in LC-MS lipidomics.

 

[1] C. Thiele, C. Papan, D. Hoelper, K. Kusserow, A. Gaebler, M. Schoene, K. Piotrowitz, D. Lohmann, J. Spandl, A. Stevanovic, A. Shevchenko, L. Kuerschner, ACS Chem. Biol. 2012, 7, 2004–2011.

[2] C. Thiele, K. Wunderling, P. Leyendecker, Nat. Methods 2019, 16, 1123–1130.

[3] F.-F. Hsu, Anal Bioanal Chem 2018, 410, 6387–6409

[4] P. Nepachalovich, S. Bonciarelli, G. Lombardi Bendoula, J. Desantis, M. Eleuteri, C. Thiele, L. Goracci, M. Fedorova, Angew. Chem. Int. Ed. 2025, e202501884.

You must be logged in to access this content. Not yet registered? Create a new account

 

 

1 2 3 4 5 … 25
Copyright © 2021 Mass Analytica. All rights reserved.