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Alcoriza-Balaguer, M. I.

Publications and source records attributed to Alcoriza-Balaguer, M. I..

2 recordsLinked to original sources

FAMetA: a mass isotopologue-based tool for the comprehensive analysis of fatty acid metabolism

The use of stable isotope tracers and mass spectrometry (MS) is the gold standard method for the analysis of fatty acids (FAs) metabolism. Yet current state-of-the-art tools provide limited and difficult to interpret information about FA biosynthetic routes. Here we present FAMetA, an R-package and a web-based application (www.fameta.es) that use 13C mass-isotopologue profiles to estimate FA import, de novo lipogenesis, elongation, and desaturation in a user-friendly platform. The FAMetA workflow covers all the functionalities needed for MS data analyses. To illustrate its utility, different in vitro and in vivo experimental settings are used in which FA metabolism is modified. Thanks to the comprehensive characterisation of FA biosynthesis and the easy-to-interpret graphical representations compared to previous tools, FAMetA discloses unnoticed insights into how cells reprogramme their FA metabolism and, when combined with FASN, SCD1 and FADS2 inhibitors, it enables the straightforward identification of new FAs by the metabolic reconstruction of their synthesis route.

systems biology↗

LipidMS 3.0: an R-package and a web-based tool for LC-MS/MS data processing and lipid annotation

SummaryLipidMS was initially envisioned to use fragmentation rules and data-independent acquisition (DIA) for lipid annotation. However, data-dependent acquisition (DDA) remains the most widespread acquisition mode for untargeted LC-MS/MS-based lipidomics. Here we present LipidMS 3.0, an R package that not only adds DDA and new lipid classes to its pipeline, but also the required functionalities to cover the whole data analysis workflow from pre-processing (i.e., peak-peaking, alignment and grouping) to lipid annotation. We applied the new workflow in the data analysis of a commercial human serum pool spiked with 68 lipid standards acquired in the full scan, DDA and DIA modes. When focusing on the detected lipid standard features and total identified lipids, LipidMS 3.0 data pre-processing performance is similar to XCMS, whereas it complements the annotations provided by MS-DIAL, one of the most widely used tools in lipidomics. To extend and facilitate LipidMS 3.0 usage among less experienced R-programming users, the workflow was also implemented as a web-based application. Availability and ImplementationThe LipidMS R-package is freely available at https://CRAN.R-project.org/package=LipidMS and as a website at http://www.lipidms.com. Contactjuancarlos_garcia@iislafe.es, agustin.lahoz@uv.es

bioinformatics↗