Multi-omic data integration for the study of production, carcass, and meat quality traits in Nellore cattle

Novais, Francisco José de; Hyeong-keun, Yu; Cesar, Aline Silva Mello; Momen, Mehdi; Poleti, Mirele Daiana; Petry, Bruna; Mourão, Gérson Barreto; Regitano, L. C. de A.; Morota, Gota; Coutinho, Luiz Lehmann

doi:10.3389/fgene.2022.948240

Cited by 2 publications

(1 citation statement)

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“…The best algorithm was then bootstrapped 1,000 times to estimate the uncertainty of the edge's strength and the direction of the network as previously described [21,22]. Edges showing presence in at least 60% (strength) among all the 1,000 models were kept in the Bayesian network through model averaging.…”

Section: Bayesian Networkmentioning

confidence: 99%

Multi-omics integration and immune profiling identify possible causal networks leading to uterine microbiome dysbiosis in dairy cows that develop metritis

Casaro,

Prim,

Gonzalez

et al. 2024

Preprint

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Background Cows that develop metritis experience dysbiosis of their uterine microbiome, where opportunistic pathogens overtake uterine commensals. Whether opportunistic pathogens thrive and cause metritis may be determined by how efficiently the immune system responds to these pathogens. Nonetheless, periparturient cows experience immune dysregulation, which seems to be intensified by prepartum obesity and lipid mobilization Herein, Bayesian networks were applied to investigate the directional correlations between prepartum body weight (BW), BW loss, pre- and postpartum systemic immune profiling and plasma metabolome, and postpartum uterine metabolome and microbiome. Results According to the directionality network, greater prepartum BW led to greater BW loss, which led to an increase in plasma fatty acids at parturition, indicating that heavier cows were in lower energy balance than lighter cows. Greater prepartum BW also led to an increase in prepartum systemic cellular death, which led to an increase in systemic inflammation, immune activation, and metabolomic changes associated with oxidative stress prepartum and at parturition, which indicates a positive directional correlation between BW and systemic inflammation. These changes led to an increase in polymorphonuclear cell extravasation postpartum, which led to an increase in uterine metabolomic changes associated with tissue damage, suggesting that excessive polymorphonuclear cell migration to the uterus leads to excessive endometrial damage. These changes led to an increase in pathogenic bacteria in cows that developed metritis, suggesting that excessive tissue damage may disrupt physical barriers or increase substrate availability for bacterial growth. Conclusions This work provides robust mechanistic hypotheses for how prepartum body weight impacts peripartum immune and metabolic profiles, leading to uterine opportunistic pathogens overgrowth and metritis development.

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Section: Bayesian Networkmentioning

confidence: 99%