Effects of insulin, recombinant bovine somatotropin, and their interaction on insulin-like growth factor-I secretion and milk protein production in dairy cows

This trial was designed to test the effects of insulin, recombinant bovine somatotropin (rbST), and their interaction on milk protein and selected blood parameters in dairy cows. Eight Holstein cows (86 +/- 10 d in milk) were divided in two groups and used in two replicates of a Latin square design with four animals, four periods, and four treatments: 1) intravenous infusion of saline, 2) infusion of saline and subcutaneous administration of 40 mg of rbST per day, 3) intravenous infusion of 12 mg of insulin per day coupled with glucose infusion, and 4) rbST administration combined with insulin and glucose infusion. The glucose infusion rate was adjusted to maintain euglycemia. Each experimental period lasted 14 d: treatments were administered during the first 6 d, and no treatment was administered during the following 8-d resting phase. The average daily amount of glucose infusion needed to avoid hypoglycemia was 2.8 kg/cow when only insulin was infused as opposed to 2.2 kg/cow when both insulin and rbST were administered, indicating that either rbST causes a peripheral resistance to insulin or rbST increased liver gluconeogenesis or both. Data from the last 3 d of infusion were analyzed by using the SAS system for mixed models. Percent protein of milk tended to be lower (2.84 vs. 2.79%) and milk urea content was lower (16.6 vs. 14.8 mg/dl) during rbST administration, regardless of insulin infusion. Insulin infusion increased percent protein (2.78 vs. 2.85%) and percent casein (2.36 vs. 2.46%) and decreased milk urea content (17.1 vs. 14.3 mg/dl) regardless of rbST administration. For milk yield, protein yield, casein yield, lactose percent, and lactose yield, there were significant interactions between insulin and rbST administration. For example, casein yield averaged 1.17, 1.12, 1.20, and 1.28 kg/d for saline, insulin, rbST, and insulin combined with rbST, respectively. Similarly, there was a significant interaction between insulin and rbST on IGF-I levels, which were 122.5, 181.3, 342.3, and 492.2 ng/ml for saline, insulin, rbST, and insulin combined with rbST, respectively. In conclusion, these results clearly demonstrated that insulin interacts with bST in early lactation to improve milk protein synthesis and yield in dairy cows. These effects are probably mediated through a combination of bST nutrient mobilization, bST-induced gluconeogenesis, bST-induced insulin peripheral resistance, and bST/insulin synergism on insulin-like growth factor-I secretion and on mammary epithelial tissue.

Toward altering milk composition by genetic manipulation: current status and challenges

The implementation of large-scale genome mapping and sequencing has improved the understanding of animal genetics. A large number of gene sequences are now available to serve as regulatory elements or genes of interest. Although the central thrust of this work is focused on understanding disease states, the manipulation of normal metabolic processes is feasible. To date, the genetic manipulation of livestock has been limited to the permanent addition of genes of clinical interest. This study explores the utility of genetically engineered cattle as a means of altering milk composition to improve the functional properties of milk, increasing marketability. Improvements would include increasing the concentration of valuable components in milk (e.g., casein), removing undesirable components (e.g., lactose), or altering composition to resemble that of human milk as a means of improving human neonatal nutrition. The protracted time lines of genetically modifying dairy cattle has prompted the development of animal models. A model for dwarf goats is discussed in terms of circumventing the lengthy time lines involved in generating transgenic cattle and allowing for an accelerated expansion of research in molecular genetics of dairy animals. Thus, the genetic manipulation of dairy cattle is feasible and could have significant impacts on milk quality, attributes of novel dairy products, and human health.

Metabolizable energy and absorbed protein requirements for milk component production

Metabolic pathways of milk component synthesis were used to estimate metabolizable energy and absorbed protein requirements for lactation. Amounts of ATP and AA used for synthesis of each component from absorbed substrates were determined. Coefficients were adjusted to account for additional inefficiencies and to define requirements in terms of dietary supply based on NRC energy requirements and N balance data. Assuming that 10% of glucose required was derived from AA, metabolizable energy and absorbed protein requirements were 6.02 Mcal and .136 kg/kg of lactose, 13.43 Mcal and .127 kg/kg of fat, and 7.57 Mcal and 1.069 kg/kg of protein, respectively; an additional .144 Mcal/kg of milk was required for milk volume. For production of milk containing 4.8% lactose, 3.5% fat, and 3.3% protein, absorbed protein required for lactose and fat may account for 14.1 and 9.6%, respectively, of total absorbed protein required for milk production. Efficiency of protein utilization for milk protein synthesis may be as high as 90% when 10% of glucose requirements must be supplied by AA. Expressing nutrient requirements for lactation on a component basis enables calculation of requirements for milk production of any composition and does not rely on correlations between major milk components.

Altering milk composition through genetic selection

The genetic relationships among carrier, fat, protein, and lactose will allow genetic alteration in any direction desired, although some changes would be much easier than others. Genetic parameters may vary somewhat between different populations, thus affecting the rates of different directions of change. In general, however, selection for an alteration in the fat:protein ratio would proceed rapidly, principally through alteration of fat concentration. Genetic alteration of composition is likely only if economic incentives for such change exist. Economic values, and therefore selection pressure, should be applied to amounts of components rather than concentrations. Recent developments in the theory of deriving economic weights for animal breeding indicate that selection indexes need to be reassessed. Although optimum breeding goals will vary somewhat, in most circumstances fat and protein yields and concentrations and the fat:protein ratio are likely to increase due to genetic selection. Only in the unlikely situation that fat has a very small or negative economic weight are other changes indicated. Lactose concentrations are unlikely to change much in any situation. Genetic variation in the composition of fat and protein, while of biological interest, is unlikely to be of more than minor importance in genetic improvement.