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ORIGINAL RESEARCH article

Front. Microbiol.
Sec. Food Microbiology
Volume 15 - 2024 | doi: 10.3389/fmicb.2024.1507537

Machine learning-enhanced Assessment of potential probiotics from Healthy Calves for the Treatment of Neonatal Calf Diarrhea

Provisionally accepted
Yuting Zhai Yuting Zhai 1Mi-Ju Kim Mi-Ju Kim 2Peixin Fan Peixin Fan 1Sharath Rajeev Sharath Rajeev 1Sunae Kim Sunae Kim 3J. Danny Driver J. Danny Driver 1Klibs N Galvao Klibs N Galvao 1Christina Boucher Christina Boucher 1Kwangcheol Casey Jeong Kwangcheol Casey Jeong 1*
  • 1 University of Florida, Gainesville, United States
  • 2 Kyung Hee University, Seoul, Republic of Korea
  • 3 Ewha Womans University, Seoul, Seoul, Republic of Korea

The final, formatted version of the article will be published soon.

    Neonatal calf diarrhea (NCD) remains a significant contributor to calf mortality within the first three weeks of life, prompting widespread antibiotic use with associated concerns about antimicrobial resistance and disruption of the calf gut microbiota. Recent research exploring NCD treatments targeting gut microbiota dysbiosis has highlighted probiotic supplementation as a promising and safe strategy for gut homeostasis. However, varying treatment outcomes across studies suggest the need for efficient treatment options. In this study, we evaluated the potential of probiotics Limosilactobacillus reuteri, formally known as Lactobacillus reuteri, isolated from healthy neonatal calves to treat NCD.Through in silico whole genome analysis and in vitro assays, we identified nine L. reuteri strains, which were then administered to calves with NCD. Calves treated with L. reuteri strains shed healthy feces and demonstrated restored gut microbiota and normal animal behavior. Leveraging a machine learning model, we evaluated microbiota profiles and identified bacterial taxa associated with calf gut health that were elevated by L. reuteri administration. These findings represent a crucial advancement towards sustainable antibiotic alternatives for managing NCD, contributing significantly to global efforts in mitigating antimicrobial resistance and promoting overall animal health and welfare.

    Keywords: Neonatal calf diarrhea, gut microbiome, machine learning, Probiotics, Host Specificity

    Received: 07 Oct 2024; Accepted: 25 Nov 2024.

    Copyright: © 2024 Zhai, Kim, Fan, Rajeev, Kim, Driver, Galvao, Boucher and Jeong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Kwangcheol Casey Jeong, University of Florida, Gainesville, United States

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.