0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      A novel Mediterranean diet-inspired supplement ameliorates cognitive, microbial, and metabolic deficits in a mouse model of low-grade inflammation

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          ABSTRACT

          The Mediterranean diet (MD) and its bioactive constituents have been advocated for their neuroprotective properties along with their capacity to affect gut microbiota speciation and metabolism. Mediated through the gut brain axis, this modulation of the microbiota may partly contribute to the neuroprotective properties of the MD. To explore this potential interaction, we evaluated the neuroprotective properties of a novel bioactive blend (Neurosyn240) resembling the Mediterranean diet in a rodent model of chronic low-grade inflammation. Behavioral tests of cognition, brain proteomic analysis, 16S rRNA sequencing, and 1H NMR metabolomic analyses were employed to develop an understanding of the gut-brain axis interactions involved. Recognition memory, as assessed by the novel object recognition task (NOR), decreased in response to LPS insult and was restored with Neurosyn240 supplementation. Although the open field task performance did not reach significance, it correlated with NOR performance indicating an element of anxiety related to this cognitive change. Behavioral changes associated with Neurosyn240 were accompanied by a shift in the microbiota composition which included the restoration of the Firmicutes: Bacteroidota ratio and an increase in Muribaculum, Rikenellaceae Alloprevotella, and most notably Akkermansia which significantly correlated with NOR performance. Akkermansia also correlated with the metabolites 5-aminovalerate, threonine, valine, uridine monophosphate, and adenosine monophosphate, which in turn significantly correlated with NOR performance. The proteomic profile within the brain was dramatically influenced by both interventions, with KEGG analysis highlighting oxidative phosphorylation and neurodegenerative disease-related pathways to be modulated. Intriguingly, a subset of these proteomic changes simultaneously correlated with Akkermansia abundance and predominantly related to oxidative phosphorylation, perhaps alluding to a protective gut-brain axis interaction. Collectively, our results suggest that the bioactive blend Neurosyn240 conferred cognitive and microbiota resilience in response to the deleterious effects of low-grade inflammation.

          GRAPHICAL ABSTRACT

          Related collections

          Most cited references74

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

            Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

              The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
                Bookmark

                Author and article information

                Journal
                Gut Microbes
                Gut Microbes
                Gut Microbes
                Taylor & Francis
                1949-0976
                1949-0984
                4 June 2024
                2024
                4 June 2024
                : 16
                : 1
                : 2363011
                Affiliations
                [a ]Norwich Medical School, Faculty of Medicine and Health Sciences, University of East Anglia; , Norwich, UK
                [b ]Activ’Inside; , Beychac et Caillau, France
                [c ]Department for Life Quality Studies, Alma Mater Studiorum, University of Bologna; , Alma, Italy
                [d ]Department of Translational Research and New Technologies in Medicine and Surgery, University of Pisa; , Pisa, Italy
                [e ]Department of Pharmacy, University G. d’Annunzio of Chieti-Pescara; , Chieti, Italy
                [f ]School of Pharmacy, University of Camerino; , Camerino, Italy
                Author notes
                CONTACT David Vauzour D.Vauzour@ 123456uea.ac.uk Norwich Medical School, Faculty of Medicine and Health Sciences, University of East Anglia, Norwich NR4 7TJ, UK
                Author information
                https://orcid.org/0000-0001-5952-8756
                Article
                2363011
                10.1080/19490976.2024.2363011
                11155709
                38835220
                2ad64044-6e4c-416a-8a57-85ac29d137af
                © 2024 The Author(s). Published with license by Taylor & Francis Group, LLC.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License ( http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

                History
                Page count
                Figures: 6, Tables: 1, References: 75, Pages: 1
                Categories
                Research Article
                Research Paper

                Microbiology & Virology
                gut-brain axis,akkermansia,neurodegenerative disease,cognition,inflammation,microbiota

                Comments

                Comment on this article