Comparative study of taxonomy abundance estimation from metagenomic data vs. 16S rRNA gene sequencing data

TY - JOUR

T1 - Comparative study of taxonomy abundance estimation from metagenomic data vs. 16S rRNA gene sequencing data

AU - Ye, Xiaoxing

AU - Satti, Maria Altaf

AU - Sahana, Goutam

AU - Lund, Mogens Sandø

AU - Cai, Zexi

PY - 2024

Y1 - 2024

N2 - Background: To study the rumen microbiome, 16S rRNA gene sequencing, and shotgun metagenomics sequencing are commonly employed methods, yet microbial and functional diversity remain underexplored. We compare 16S rRNA, gene sequencing, and shotgun metagenomics sequencing to assess their influence on detecting microbial communities and functions in the rumen, using rumen samples from 500 Holstein cows from one single farm. Result: At the genus level, both methods showed similar dominant taxa, while metagenomics identified 169 species compared to 19 species observed by 16S sequencing. Similar trends in alpha and beta diversity across sequencing techniques of both microbiome composition and functions. A strong positive correlation (0.83) was found between 16S and metagenomics data, particularly for key genera such as Methanobrevibacter, Methanosphaera, Prevotella, and Succiniclasticum. Co-occurrence network analysis identified central microbial genera Methanomethylophilus, Prevotella, Methanobrevibacter and Succiniclasticum in the metagenomics and 16S datasets. Prevotella group species of metagenomics sequencing were key nodes of co-occurrence network. Functional profiling based on the KEGG database identified more KEGG Orthology (KO) entries in the metagenomics dataset compared to 16S. Common pathways were associated with Metabolism, Genetic information processing, and Transporters. Moreover, strong correlations between 16S and metagenomics functions (0.85) were also observed. Conclusion: These findings highlight the advantages of metagenomics in providing a comprehensive view of microbial communities, offering valuable insights for optimizing sequencing techniques in rumen microbiome research.

AB - Background: To study the rumen microbiome, 16S rRNA gene sequencing, and shotgun metagenomics sequencing are commonly employed methods, yet microbial and functional diversity remain underexplored. We compare 16S rRNA, gene sequencing, and shotgun metagenomics sequencing to assess their influence on detecting microbial communities and functions in the rumen, using rumen samples from 500 Holstein cows from one single farm. Result: At the genus level, both methods showed similar dominant taxa, while metagenomics identified 169 species compared to 19 species observed by 16S sequencing. Similar trends in alpha and beta diversity across sequencing techniques of both microbiome composition and functions. A strong positive correlation (0.83) was found between 16S and metagenomics data, particularly for key genera such as Methanobrevibacter, Methanosphaera, Prevotella, and Succiniclasticum. Co-occurrence network analysis identified central microbial genera Methanomethylophilus, Prevotella, Methanobrevibacter and Succiniclasticum in the metagenomics and 16S datasets. Prevotella group species of metagenomics sequencing were key nodes of co-occurrence network. Functional profiling based on the KEGG database identified more KEGG Orthology (KO) entries in the metagenomics dataset compared to 16S. Common pathways were associated with Metabolism, Genetic information processing, and Transporters. Moreover, strong correlations between 16S and metagenomics functions (0.85) were also observed. Conclusion: These findings highlight the advantages of metagenomics in providing a comprehensive view of microbial communities, offering valuable insights for optimizing sequencing techniques in rumen microbiome research.

KW - Rumen microbiome

KW - Sequencing techniques

KW - microbial diversity

KW - functional diversity

KW - co-occurrence network

KW - KEGG

M3 - Journal article

SN - 2049-2618

JO - Microbiome

JF - Microbiome

ER -