Abstract #T146
Section: Lactation Biology (posters)
Session: Lactation Biology II
Format: Poster
Day/Time: Tuesday 7:30 AM–9:30 AM
Location: Exhibit Hall A
Session: Lactation Biology II
Format: Poster
Day/Time: Tuesday 7:30 AM–9:30 AM
Location: Exhibit Hall A
# T146
Varying the ratio of Lys:Met while maintaining the ratios of Thr:Phe, Lys:Thr, Lys:His, and Lys:Val alters bovine mammary cell transcriptome profiles measured by RNAsequencing.
Xianwen Dong1,2, Zheng Zhou*3, Ariane Helmbrecht4, Claudia Parys4, Z. Wang2, Juan J. Loor1, 1University of Illinois, Urbana, IL, 2Sichuan Agricultural University, Ya'an, Sichuan Province, China, 3Clemson University, Clemson, SC, 4Evonik Nutrition & Care GmbH, Hanau-Wolfgang, Germany.
Key Words: milk protein, transcriptomics, bioinformatics
Varying the ratio of Lys:Met while maintaining the ratios of Thr:Phe, Lys:Thr, Lys:His, and Lys:Val alters bovine mammary cell transcriptome profiles measured by RNAsequencing.
Xianwen Dong1,2, Zheng Zhou*3, Ariane Helmbrecht4, Claudia Parys4, Z. Wang2, Juan J. Loor1, 1University of Illinois, Urbana, IL, 2Sichuan Agricultural University, Ya'an, Sichuan Province, China, 3Clemson University, Clemson, SC, 4Evonik Nutrition & Care GmbH, Hanau-Wolfgang, Germany.
The objective of this study was to determine the influence of increasing supplemental Met, based on the ideal 2.9:1 ratio of Lys to Met, on mammary cell transcriptome profiles. MAC-T cells, an immortalized bovine mammary epithelial cell line, were incubated (n = 5 replicates/treatment) for 12 h with 3 incremental doses of Met while holding Lys concentration constant to achieve the following: Lys:Met 2.9:1 (ideal AA ratio; IPAA), Lys:Met 2.5:1 (LM2.5), and Lys:Met 2.0:1 (LM2.0). The ratios of Thr:Phe (1.05:1), Lys:Thr (1.8:1), Lys:His (2.38:1), and Lys:Val (1.23:1) were the same across the 3 treatments. Extracted total RNA was sequenced using the Illumina platform, and mapped to the Bos taurus genome assembly (UMD_3.1.1). Statistical analysis was conducted using the Bioconductor edgeR package, with treatment as fixed effect. The Dynamic Impact Approach software was used to uncover the most-impacted cellular pathways. Analysis of variance at a False Discovery Rate (FDR) of 0.15 and raw P-value <0.01 identified 687 differentially expressed genes (DEG) in response to changes in Met level. When compared with IPAA, the bioinformatics analysis using the DEG revealed unique responses to LM2.5, including an overall downregulation of some metabolic pathways (ketone body metabolism, galactose metabolism, pentose phosphate), and upregulation of glycosphingolipid biosynthesis and fatty acid synthesis. Fewer pathways were downregulated when comparing LM2.0 with IPAA, and among the top were antigen processing and presentation, protein processing in the ER, and steroid biosynthesis. Compared with the effect caused by LM2.5, a greater number of metabolic and signaling pathways were upregulated by LM2.0 relative to IPAA including apoptosis, glycerolipid metabolism, glutathione metabolism, MAPK signaling, and PPAR signaling. Overall, preliminary evaluation indicates that increased methionine supply can elicit changes in mammary cell transcriptome profiles. The relevance of these changes to mammary cell function in vivo remains to be determined.
Key Words: milk protein, transcriptomics, bioinformatics