Calabrese, V. | bioRxiv Science

bioRxiv2025

Astringent flavanol fires the locus-noradrenergic system, regulating neurobehavior and autonomic nerves

Astringent flavanols (FLs) have shown enhanced cognitive function in a large intervention trial, but their mechanism remains unclear due to poor bioavailability. An oral dose of FLs increased spontaneous locomotion and memory, with activation of the sympathetic-adrenergic-medullary (SAM) and hypothalamic-pituitary-adrenal (HPA) axis, as shown by increased urinary catecholamine concentrations and corticotropin-releasing hormone (CRH) mRNA expression in the paraventricular nucleus (PVN) of mice. MS imaging showed high intensity of noradrenaline (NA) in the locus coeruleus (LC), which plays a key role in learning and memory, the hypothalamus lateral preoptic area, which affects sleep and arousal, and the brainstem as the origin of the sympathetic nervous system, immediately after FLs administration. Subsequent in situ hybridization (ISH) analysis showed that these NAs originated from LC. Astringent compounds like FLs influence brain function and physiological changes. Furthermore, the present series of results presents novel mechanisms by which food sensory properties maintain homeostasis. Highlights- A oral dose of astringent flavanols (FLs) immediately fires locus coeruleus-noradrenaline axis - FLs enhance spontaneous locomotion and short-term memory in mice - SAM and HPA axis are also activated by an oral dose of FLs - FLs astringency affects the brain and body, contributing to homeostasis.

synthetic biology↗

bioRxiv2023

Concomitant investigation of crustacean amphipods lipidome and metabolome during molting stage by Zeno SWATH Data-Independent Acquisition coupled with Electron Activated Dissociation and machine learning

BackgroundDIA (Data-Independent Acquisition) is a powerful technique in Liquid Chromatography coupled with high-resolution tandem Mass Spectrometry (LC-MS/MS) in metabolomics and lipidomics, for comprehensive profiling of molecules in biological samples. It provides unbiased coverage, improved reproducibility, and quantitative accuracy compared to Data-Dependent Acquisition (DDA). Combined with the Zeno trap and Electron-Activated Dissociation (EAD), DIA enhances data quality and structural elucidation compared to conventional fragmentation under CID. These tools were applied to study the lipidome and metabolome of the freshwater amphipod Gammarus fossarum, successfully discriminating stages and highlighting significant biological features. Despite being underused, DIA, along with the Zeno trap and EAD, holds great potential for advancing research in the omics field. ResultsDIA combined with the Zeno trap enhances detection reproducibility compared to conventional DDA, improving fragmentation spectra quality and putative identifications. LC coupled with Zeno-SWATH-DIA methods were used to study molecular changes in reproductive cycle of female gammarids. Multivariate data analysis including Principal Component Analysis and Partial Least Square Discriminant Analysis successfully identified statistically significant features responsible for group segregation. EAD fragmentation helped to identify unknown features and to confirm their molecular structure using fragmentation spectra DB annotation or machine learning. EAD database matching accurately annotated five glycerophospholipids, including the position of double bonds on fatty acid chain moieties. SIRIUS database predicted structures of unknown features based on experimental fragmentation spectra to compensate for database incompleteness. SignificanceReproducible detection of features and confident identification of putative compounds are pivotal stages within analytical pipelines. The DIA approach combined with Zeno pulsing and EAD synergistically enhances detection sensitivity while providing orthogonal fragmentation information, thereby facilitating a comprehensive and insightful exploration of pertinent biological molecules associated with the reproductive cycle of gammarids. The developed methodology holds great promises for identifying biomarkers of significance in the field of environmental assessment. HighlightsO_LIAdvancements in Data-Independent-Acquisition methods for lipidomics and metabolomics. C_LIO_LIZeno pulsing improves sensitivity in fragment detection and compound identification. C_LIO_LIComprehensive structure elucidation of lipids and metabolites using EAD fragmentation. C_LI

biochemistry↗