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Lookup NU author(s): Cassie Bakshani, Professor William WillatsORCiD
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).
© The Author(s) 2025.While rapid progress has been made to characterize the bacterial and archaeal populations of the rumen microbiome, insight into how they interact with keystone protozoal species remains elusive. Here, we reveal two distinct system-wide rumen community types (RCT-A and RCT-B) that are not strongly associated with host phenotype nor genotype but instead linked to protozoal community patterns. We leveraged a series of multi-omic datasets to show that the dominant Epidinium spp. in animals with RCT-B employ a plethora of fiber-degrading enzymes that present enriched Prevotella spp. a favorable carbon landscape to forage upon. Conversely, animals with RCT-A, dominated by genera Isotricha and Entodinium, harbor a more even distribution of fiber, protein, and amino acid metabolizers, reflected by higher detection of metabolites from both protozoal and bacterial activity. Our results indicate that microbiome variation across key protozoal and bacterial populations is interlinked, which should act as an important consideration for future development of microbiome-based technologies.
Author(s): Kobel CM, Leu A, Vera-Ponce de Leon A, Oyas O, Lai W, Altshuler I, Hagen LH, Wollenberg RD, Sondergaard MT, Bakshani CR, Willats WGT, Nicoll L, McIlroy SJ, Hvidsten TR, Schmidt O, Greening C, Tyson GW, Roehe R, Aho VTE, Pope PB
Publication type: Article
Publication status: Published
Journal: Nature Communications
Year: 2025
Volume: 16
Issue: 1
Online publication date: 07/07/2025
Acceptance date: 18/06/2025
Date deposited: 21/07/2025
ISSN (electronic): 2041-1723
Publisher: Nature Research
URL: https://doi.org/10.1038/s41467-025-61302-2
DOI: 10.1038/s41467-025-61302-2
Data Access Statement: See Supplementary Data 1c. The DNA and RNA data generated are deposited in the European Nucleotide Archive (ENA) database under accession code PRJEB83989, the proteomic data in the Proteomics Identifications Database (PRIDE) under accession code PXD061198, and the untargeted metabolomic data in the MetaboLights database under accession code MTBLS12283. Animal metadata and processed omics data, including Metagenome Assembled Genomes (MAGs), are available through the Norwegian Research Infrastructure Services at (https://ns9864k.web.sigma2.no/TheMEMOLab/projects/ SupaCow/data_for_publication/). The Bos taurus genome data is available as NCBI Bioproject PRJNA391427, the Entodinium caudatum genome as PRJNA380643, and the protozoal Single Amplified Genomes (SAGs) as PRJNA777442. R scripts used are available at https://github.com/TheMEMOLab/supacow-share89. The code to perform proteomic network analysis using WGCNA is available at https:// github.com/cmkobel/holodoublevu90.
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