Postdoctoral fellow, University of Alberta
Bovine milk is an important food source for human consumption, and the high demand for milk due to the human population growth represents a key component of food security issues. Forage is the most important and variable input in dairy production, and forage quality exerts large effects on the health and productive performance of dairy cows and the quality of milk. To date, most studies have focused on the improvement of dairy nutritional management strategies to enhance milk production and quality, whereas the physiological and metabolic mechanisms involved have not been well examined. Since the beginning of 21st century, a shortage of high-quality forage has led to a bottleneck for the development of the dairy industry in China as well as many other countries. As the corn grain’s by-products, corn stover is one of the most abundant feed resources , and it is widely used in many small dairy operations with low cost. However, the nutritional constraints of corn stover (CS), such as the lower content of crude protein and easy-to-use carbohydrates when compared to alfalfa, limit its use in modern dairy farms with high productivity. Due to such limitation, the nowadays dairy industry has largely relied on importing alfalfa, while 80 million tons of CS have been disposed every year. Therefore, understanding the physiological and metabolic mechanisms involved in milk production under low-quality forage is helpful to developing strategies for reasonable and efficient utilization of the abundant cereal straw and stover sources in milk production. Recently developed “omics” technologies make it possible to comprehensively and systematically study lactation at the levels of DNA, RNA, proteins, and metabolites and to identify the most important factors or processes that may influence lactation. Genomics not only maps the genes but also performs sequence analysis to provide insights into the coding gene heterogeneity. Transcriptomics can simultaneously profile several to more than thousands of mRNA expression levels and changes. The proteomic tools are used to determine the changes in protein expression patterns, abundance, and post-translational modifications. Moreover, metabolomics technology has been used to analyze large groups of metabolites in biological samples that can reflect the physicochemical properties of the body.
Abstract: This experiment assessed the utilization of amino acids (AA) by the mammary gland of cows when diets are changed from an alfalfa hay-based diet (AH) to cereal straw-based diets using corn stover (CS) or rice straw (RS). Thirty multiparous Holstein dairy cows were selected and randomly assigned to 1 of 3 treatments (n = 10). After 13 weeks’ feeding, arterial and venous plasma were collected every 6 hours over 2 days and AA concentrations measured. The cows fed the CS or RS diet had lower milk and protein yield despite similar dry matter intake. The digestive AA flow was predicted to be lower in the cows fed CS or RS than in AH-fed cows. The arterial concentration of methionine and valine was lower in the cows fed RS than in cows fed AH. The mammary uptake of most essential AA, especially branched-chain AA, methionine, and arginine, was greater in the AH-fed cows than in cows fed CS or RS. The ratio of mammary uptake to milk output of methionine was lower in the RS-fed cows than that in the cows fed AH, with a value below 1 for both. In summary, the insufficient supply of free AA from arterial plasma presented to the mammary gland and lower mammary plasma flow restrict the mammary AA uptake for milk protein synthesis when energy is limited. On the other hand, the utilization of leucine and methionine may be a limiting factor for milk protein synthesis and lactation performance when corn stover or rice straw is fed to dairy cows.
Pub.: 27 Apr '16, Pinned: 28 Aug '17
Abstract: In this study, we investigated the molecular regulatory mechanisms of milk protein production in dairy cows by studying the miRNAomes of five key metabolic tissues involved in protein synthesis and metabolism from dairy cows fed high- and low-quality diets. In total, 340, 338, 337, 330, and 328 miRNAs were expressed in the rumen, duodenum, jejunum, liver, and mammary gland tissues, respectively. Some miRNAs were highly correlated with feed and nitrogen efficiency, with target genes involved in transportation and phosphorylation of amino acid (AA). Additionally, low-quality forage diets (corn stover and rice straw) influenced the expression of feed and nitrogen efficiency-associated miRNAs such as miR-99b in rumen, miR-2336 in duodenum, miR-652 in jejunum, miR-1 in liver, and miR-181a in mammary gland. Ruminal miR-21-3p and liver miR-2285f were predicted to regulate AA transportation by targeting ATP1A2 and SLC7A8, respectively. Furthermore, bovine-specific miRNAs regulated the proliferation and morphology of rumen epithelium, as well as the metabolism of liver lipids and branched-chain AAs, revealing bovine-specific mechanisms. Our results suggest that miRNAs expressed in these five tissues play roles in regulating transportation of AA for downstream milk production, which is an important mechanism that may be associated with low milk protein under low-quality forage feed.
Pub.: 18 Feb '16, Pinned: 28 Aug '17
Abstract: Alfalfa hay and corn stover are different type of forages which can significantly impact a cow’s lactation performance, but the underlying metabolic mechanism has been poorly studied. We used biomarker and pathway analyses to characterize related biomarkers and pathways based on urine metabolomics data from different forage treatments. Urine was collected from 16 multiparous Holstein dairy cows fed alfalfa hay (AH, high-quality forage, n = 8) and corn stover (CS, low-quality forage, n = 8) respectively. Gas chromatography–time of flight/mass spectrometry (GC-TOF/MS) was performed to identify metabolites in urine and the metaboanalyst online platform was used to do biomarker and pathway analysis.Hippuric acid (HUA) and N-methyl-glutamic (NML-Glu) indicated the most significant difference between the two diets, when statistically validated by biomarker analysis. HUA was also validated by standard compound quantitative method and showed significant higher concentration in CS group than AH group (2.8282 vs. 0.0005 mg/mL; P < 0.01). The significant negative correlation between milk yield and HUA (R2 = 0.459; P < 0.01) and significant positive correlation between milk yield and NML-Glu (R2 = 0.652; P < 0.01) were characterized. The pathway analysis revealed that these different metabolites were involved in 17 pathways including 7 influential pathways (pathway impact value > 0): Tyr metabolism, starch and sucrose metabolism, amino sugar and nucleotide sugar metabolism, galactose metabolism, Phe, Tyr and Try biosynthesis, purine metabolism, and glycerolipid metabolism. Based on the metabolome view map, the Phe, Tyr and Try biosynthesis pathway exhibited the highest impact value (0.50), and the Holm-Bonferroni multiple testing-based analysis revealed the most significant difference in the Tyr metabolism pathway (Holm P = 0.048).The identified HUA and NML-Glu may serve as potential biomarkers for discriminating CS and AH diets and could be used as candidates for milk yield related mechanistic investigations. Integrated network pathways associated with related metabolites provide a helpful perspective for discovering the effectiveness of forage quality in lactation performance and provides novel insights into developing strategies for better utilization of CS and other low-quality forage in China.
Pub.: 31 Aug '16, Pinned: 28 Aug '17
Abstract: The fundamental understanding of the mechanisms regulating milk protein synthesis is limited. This study aimed to elucidate the metabolic mechanisms of milk production affected by forage quality through studying metabolites from four biofluids (rumen fluid, milk, serum, and urine) collected from 16 lactating cows fed alfalfa hay (AH, high-quality, n = 8) and corn stover (CS, low-quality, n = 8) using gas chromatography-time-of-flight/mass spectrometry. The cows fed AH exhibited higher milk yield (P < 0.01), milk protein yield (P = 0.04), and milk efficiency (P < 0.01) than those fed CS. A total of 165, 195, 218, and 156 metabolites were identified in the rumen fluid, milk, serum, and urine, respectively, while 29 metabolites were found in all four biofluids. In addition 55, 8, 28, and 31 metabolites in each biofluid were significantly different (VIP > 1 and P < 0.05) between the AH- and CS-fed animals. These metabolites were involved in glycine, serine, and threonine metabolism; tyrosine metabolism; and phenylalanine metabolism. Further integrated key metabolic pathway analysis showed that the AH-fed cows may have more comprehensive amino acid metabolisms, suggesting that these metabolite-associated pathways may serve as biomarkers for higher milk yield and better milk protein quality.
Pub.: 20 Jan '15, Pinned: 28 Aug '17
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