Integration of multi-tissue transcriptomics and microbiome data to assess the effects of alternative feed on methane production and other phenotypes in cattle

Author(s)

Anna Carolina Fernandes

• Document type: Doctoral Thesis
• Press: Piracicaba.
• Institution: Universidade de São Paulo (USP). Escola Superior de Agricultura Luiz de Queiroz (ESALA/BC)
• Defense date: 2024-12-02

Examining board members

Luiz Lehmann Coutinho; Luciana Correia de Almeida Regitano; Antonio Reverter Gómez

• Advisor: Luiz Lehmann Coutinho

Abstract

In today\'s agricultural context, achieving a harmonious balance between sustainable livestock practices, economic efficiency, and environmental stewardship is paramount for global food security. This thesis addresses pressing challenges in livestock farming, particularly the escalating costs of feed, by exploring an alternative dietary strategy aimed at reducing feed costs while optimizing animal performance and environmental sustainability. Focusing on Nellore cattle, we investigated how dietary inputs can affect economically relevant phenotypic traits such as growth, carcass quality, and methane emissiona significant contributor to greenhouse gas levelsas well as the intricate ecosystems within fecal and ruminal microbiomes. These microbial communities play pivotal roles in nutrient metabolism and methane production, thus influencing both animal productivity and environmental resilience. In this context, we proposed a novel strategy to assess how diet impacts animal production by employing a multi-tissue gene co-expression and microbial coabundance network approach. This allowed us to reveal how dietary modifications could induce changes in gene expression patterns associated with phenotypes of interest and microbial composition. By integrating extensive datasets from transcriptome and metagenome analyses, we aimed to uncover regulatory mechanisms governing production efficiency phenotypes and microbial dynamics. Our results demonstrated significant phenotypic differences in favour of the alternative diet, including higher average daily weight gain at finishing, higher dry matter intake at finishing, lower methane emission, higher carcass yield, and higher subcutaneous fat thickness at the rib-eye muscle area. Additionally, we found that methane emissions were uniquely linked to different genes and microbial genera for each diet. Furthermore, distinct microbial genera responded uniquely to each dietary condition, with significant shifts in microbial connectivity observed, particularly for genera such as Megasphaera and Butyrivibrio. These insights promise to inform the development of optimized feed formulations and refined management practices. Such advancements are designed to enhance both the economic viability and environmental sustainability of beef production systems. Ultimately, this thesis contributes to a deeper understanding of how diet interventions can influence livestock outcomes while mitigating environmental impacts. Moreover, the merit of our network analysis lies in its ability to comprehensively explore the complex interactions between diet, gene expression, and microbial composition, providing a robust framework for assessing the effects of dietary changes on animal production and sustainability. By elucidating these complex interactions, our research supports evidence-based strategies for sustainable intensification in global beef production. In conclusion, our findings highlight the potential for dietary interventions to significantly enhance both production efficiency and environmental sustainability in beef cattle farming. In addition, the network analysis strategy developed in this thesis provides a valuable tool for future research and practical applications in livestock nutrition and management. (AU)

• FAPESP's process: 21/14321-0 - Construction of gene co-expression networks correlated to ruminal microorganisms profile, feed efficiency and intramuscular fat deposition in Nelore cattle
• Grantee: Anna Carolina Fernandes
• Support Opportunities: Scholarships in Brazil - Doctorate