Discovering non-polar metabolites markers of performance and feed efficiency from Nelore bulls.

• Grant number: 24/08279-9
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: December 01, 2024
• End date: January 31, 2026
• Field of knowledge: Biological Sciences - Biology
• Principal Investigator: Luciana Correia de Almeida Regitano
• Grantee: Ousmane Diarra
• Host Institution: Embrapa Pecuária Sudeste. Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA). Ministério da Agricultura, Pecuária e Abastecimento (Brasil). São Carlos , SP, Brazil
• Associated research grant: 19/04089-2 - The Nelore hologenome: implications in beef quality and feed efficiency, AP.ESCIENCE.TEM

Abstract

Brazil has the second-largest commercial cattle herd in the world, estimated at 244 million head. The Nelore breed (Bos indicus) is the most important beef cattle breed in the country, representing alone or in crossbreeds approximately 80% of the national herd, mainly due to its adaptability to the tropical climate and its greater resistance to parasites. Ruminants have a complex functioning digestive system due in particular to the diversity of diets and the transformations that take place throughout the stomach under the action of microbial populations. At this level, lipid metabolism plays a determining role in the quantity and especially the proportion of fatty acids available for lipid synthesis in the body. This study aims to determine non-polar (lipid) metabolites that may constitute performance markers of feed efficiency in Nelore steers, as well as proxies for the active gut microbiota. Fecal samples collected in 2020 following the bulls' performance test, during the fattening period will be used. The total fat content of feces will be determined according to the Folch method with some modifications. Fecal samples will be analyzed using a triplicate technique. Non-polar metabolites will be analyzed by the MIXED procedure available in the SAS statistical program (SAS Institute, Cary, NC, USA, 2011). The statistical model includes pen as a fixed effect and initial and final feedlot weight as covariates. Metabolite results will be considered significant when P < 0.05. Then, the data will be analyzed on the MetaboAnalyst 4.0 platform (http://www.metaboanalyst). Results will be interpreted in light of other multiomics data collected in the thematic project (microbiome profiling, host miRNAs).