1887

Abstract

Tall fescue KY-31 is an important primary forage for beef cattle. It carries a fungal endophyte that produces ergovaline, the main cause of tall fescue toxicosis that leads to major revenue loss for livestock producers. The MaxQ, an engineered cultivar, hosts an ergovaline nonproducing strain of the fungus and consequently is nontoxic. However, it is less attractive economically. It is not known how rumen microbiome processes these two forages towards nutrient generation and ergovaline transformation. We have analysed the rumen microbiome compositions of cattle that grazed MaxQ with an intervening KY-31 grazing period using the 16S rRNA-V4 element as an identifier and found that KY-31 remodelled the microbiome substantially, encompassing both cellulolytic and saccharolytic functions. The effect was not evident at the whole microbiome levels but was identified by analysing the sessile and planktonic fractions separately. A move from MaxQ to KY-31 lowered the Firmicutes abundance in the sessile fraction and increased it in planktonic part and caused an opposite effect for Bacteroidetes, although the total abundances of these dominant rumen organisms remained unchanged. The abundances of , which degrades less degradable fibres, and certain cellulolytic Firmicutes such as and 2, dropped in the sessile fraction, and these losses were apparently compensated by increased occurrences of and specific and . A return to MaxQ restored the original Firmicutes and Bacteroidetes distributions. However, several KY-31 induced changes, such as the low abundance of and two remained in place, and their substitutes maintained significant presence. The rumen microbiome was distinct from previously reported faecal microbiomes. In summary, KY-31 and MaxQ were digested in the cattle rumen with distinct consortia and the KY-31-specific features were dominant. The study also identified candidate ergovaline transforming bacteria. It highlighted the importance of analysing sessile and planktonic fractions separately.

Funding
This study was supported by the:
  • Genetics, Bioinformatics, and Computational Biology Ph.D. Program of the Virginia Tech (Award Graduate Fellowship)
    • Principle Award Recipient: BelaHaifa Khairunisa
  • Agricultural Experiment Station Hatch Program at Virginia Tech (Award CRIS project VA-160151)
    • Principle Award Recipient: BiswarupMukhopadhyay
  • College of Agriculture and Life Sciences, Virginia Polytechnic Institute and State University (Award Pratt Endowment Fellowship)
    • Principle Award Recipient: BelaHaifa Khairunisa
  • College of Agriculture and Life Sciences, Virginia Polytechnic Institute and State University (Award Pratt Endowment grant)
    • Principle Award Recipient: ChristopherD Teutsch
  • College of Agriculture and Life Sciences, Virginia Polytechnic Institute and State University (Award Pratt Endowment grant)
    • Principle Award Recipient: BrianT Campbell
  • College of Agriculture and Life Sciences, Virginia Polytechnic Institute and State University (Award Pratt Endowment grant)
    • Principle Award Recipient: BiswarupMukhopadhyay
  • Virginia Research and Extension Innovation Initiative and Virginia Cooperative Extension at Virginia Tech (Award Capacity Building grant)
    • Principle Award Recipient: BrianT Campbell
  • Virginia Research and Extension Innovation Initiative and Virginia Cooperative Extension at Virginia Tech (Award Capacity Building grant)
    • Principle Award Recipient: BiswarupMukhopadhyay
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2022-02-24
2024-07-24
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