Articles producció científica> Bioquímica i Biotecnologia

Multiomic approach to analyze infant gut microbiota: Experimental and analytical method optimization

  • Identification data

    Identifier: imarina:9224854
    Authors:
    Torrell HCanela NCereto-Massagué AKazakova PGarcía LPalacios H
    Abstract:
    Background: The human intestinal microbiome plays a central role in overall health status, especially in early life stages. 16S rRNA amplicon sequencing is used to profile its taxonomic composition; however, multiomic approaches have been proposed as the most accurate methods for study of the complexity of the gut microbiota. In this study, we propose an optimized method for bacterial diversity analysis that we validated and complemented with metabolomics by analyzing fecal samples. Methods: Forty-eight different analytical combinations regarding (1) 16S rRNA variable region sequencing, (2) a feature selection approach, and (3) taxonomy assignment methods were tested. A total of 18 infant fecal samples grouped depending on the type of feeding were analyzed by the proposed 16S rRNA workflow and by metabolomic analysis. Results: The results showed that the sole use of V4 region sequencing with ASV identification and VSEARCH for taxonomy assignment produced the most accurate results. The application of this workflow showed clear differences between fecal samples according to the type of feeding, which correlated with changes in the fecal metabolic profile. Conclusion: A multiomic approach using real fecal samples from 18 infants with different types of feeding demonstrated the effectiveness of the proposed 16S rRNA-amplicon sequencing workflow.
  • Others:

    Author, as appears in the article.: Torrell H; Canela N; Cereto-Massagué A; Kazakova P; García L; Palacios H
    Department: Bioquímica i Biotecnologia
    URV's Author/s: Cereto Massagué, Adrián José
    Keywords: Next-generation sequencing Multiomics approach Microbiome Metagenomics Metabolomics Ion torrent Early infancy microbiome
    Abstract: Background: The human intestinal microbiome plays a central role in overall health status, especially in early life stages. 16S rRNA amplicon sequencing is used to profile its taxonomic composition; however, multiomic approaches have been proposed as the most accurate methods for study of the complexity of the gut microbiota. In this study, we propose an optimized method for bacterial diversity analysis that we validated and complemented with metabolomics by analyzing fecal samples. Methods: Forty-eight different analytical combinations regarding (1) 16S rRNA variable region sequencing, (2) a feature selection approach, and (3) taxonomy assignment methods were tested. A total of 18 infant fecal samples grouped depending on the type of feeding were analyzed by the proposed 16S rRNA workflow and by metabolomic analysis. Results: The results showed that the sole use of V4 region sequencing with ASV identification and VSEARCH for taxonomy assignment produced the most accurate results. The application of this workflow showed clear differences between fecal samples according to the type of feeding, which correlated with changes in the fecal metabolic profile. Conclusion: A multiomic approach using real fecal samples from 18 infants with different types of feeding demonstrated the effectiveness of the proposed 16S rRNA-amplicon sequencing workflow.
    Thematic Areas: Química Molecular biology Materiais General medicine Farmacia Ensino Biochemistry & molecular biology Biochemistry
    licence for use: https://creativecommons.org/licenses/by/3.0/es/
    Author's mail: adrianjose.cereto@urv.cat
    Record's date: 2024-07-27
    Papper version: info:eu-repo/semantics/publishedVersion
    Link to the original source: https://www.mdpi.com/2218-273X/11/7/999
    Licence document URL: https://repositori.urv.cat/ca/proteccio-de-dades/
    Papper original source: Biomolecules. 11 (7):
    APA: Torrell H; Canela N; Cereto-Massagué A; Kazakova P; García L; Palacios H (2021). Multiomic approach to analyze infant gut microbiota: Experimental and analytical method optimization. Biomolecules, 11(7), -. DOI: 10.3390/biom11070999
    Article's DOI: 10.3390/biom11070999
    Entity: Universitat Rovira i Virgili
    Journal publication year: 2021
    Publication Type: Journal Publications
  • Keywords:

    Biochemistry,Biochemistry & Molecular Biology,Molecular Biology
    Next-generation sequencing
    Multiomics approach
    Microbiome
    Metagenomics
    Metabolomics
    Ion torrent
    Early infancy microbiome
    Química
    Molecular biology
    Materiais
    General medicine
    Farmacia
    Ensino
    Biochemistry & molecular biology
    Biochemistry
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