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A static model to analyze carbon and nitrogen partitioning in the mammary gland of lactating sows

Authors :
Hélène Quesnel
N. Le Floc’h
Aude Simongiovanni
J. van Milgen
U. Krogh
Physiologie, Environnement et Génétique pour l'Animal et les Systèmes d'Elevage [Rennes] (PEGASE)
AGROCAMPUS OUEST
Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
AJINOMOTO
Source :
animal, animal, Published by Elsevier (since 2021) / Cambridge University Press (until 2020), 2021, 15 (1), pp.100049. ⟨10.1016/j.animal.2020.100049⟩, Animal, Vol 15, Iss 1, Pp 100049-(2021), Animal, Animal, Published by Elsevier (since 2021) / Cambridge University Press (until 2020), 2021, 15 (1), pp.100049. ⟨10.1016/j.animal.2020.100049⟩
Publication Year :
2021
Publisher :
HAL CCSD, 2021.

Abstract

International audience; Quantitative estimates of mammary nutrient inputs, outputs and metabolism in sows are scarce, despite being critical elements to identify parameters controlling milk synthesis central for the feeding of lactating sows. The objective of this study was to quantify the mammary gland input and output of nutrients as well as the intramammary partitioning of carbon and nitrogen with the purpose to identify mechanisms controlling mammary nutrient inputs, metabolism and milk production in lactating sows. A data set was assembled by integration of results from four studies. The data set included data on litter performance, mammary arterial-venous concentration differences (AV-difference) of energy metabolites and amino acids, and the contents of lactose, fat and amino acids in milk. Milk yield was estimated based on average litter size and litter gain, and mammary plasma flow (MPF) was estimated using the sum of phenylalanine and tyrosine as internal flow markers. The yield and composition of milk were used to estimate mammary nutrient output in milk, and MPF and AV-difference were used to estimate net mammary input of carbon and nitrogen and output of CO 2. Carbon and nitrogen used for the synthesis of lactose, fat and protein in milk and CO 2-yielding processes were represented in a static nutrient partitioning model. The origin of mammary CO 2 output was calculated using theoretical estimates of carbon released in processes supporting mammary synthesis of de novo fat, protein and lactose in milk, mammary tissue protein turnover and transport of glucose and amino acids. Results indicated that total input of carbon from glucose and lactate was partitioned into lactose (36%), fat (31%) and CO 2yielding processes (34%). Theoretical CO 2 estimates indicated that de novo fat synthesis, milk protein synthesis and mammary tissue protein turnover were the main processes related to mammary CO 2 production. More than 90% of mammary gland amino acid input was used for milk protein. The quadratic relationship between AV-difference and mammary input of essential amino acids indicated that both changes in AV-difference and MPF contributed to the regulation of mammary input of essential amino acids. The impact of the arterial supply of amino acids on mammary input may be greater for the branched-chain amino acids, arginine and phenylalanine than for other essential amino acids. In conclusion, relationships between input and output parameters indicate that AV-difference and MPF regulate mammary nutrient input to match the supply and demand of nutrients for the mammary gland.

Details

Language :
English
ISSN :
17517311 and 1751732X
Database :
OpenAIRE
Journal :
animal, animal, Published by Elsevier (since 2021) / Cambridge University Press (until 2020), 2021, 15 (1), pp.100049. ⟨10.1016/j.animal.2020.100049⟩, Animal, Vol 15, Iss 1, Pp 100049-(2021), Animal, Animal, Published by Elsevier (since 2021) / Cambridge University Press (until 2020), 2021, 15 (1), pp.100049. ⟨10.1016/j.animal.2020.100049⟩
Accession number :
edsair.doi.dedup.....124bc4a25cbd781af3fb7ced6281363e
Full Text :
https://doi.org/10.1016/j.animal.2020.100049⟩