Methods for Collecting Milk from Mice

Mouse models offer unique opportunities to study mammary gland biology and lactation. Phenotypes within the mammary glands, especially those caused by genetic modification, often arise during lactation, and their study requires the collection of adequate volumes of milk. We describe two approaches for collecting milk from lactating mice. Both methods are inexpensive, are easy to use in the laboratory or classroom, are non-invasive, and yield adequate volumes of milk for subsequent analyses

Development of a biosensor for urea assay based on amidase inhibition, using an ion-selective electrode

A biosensor for urea has been developed based on the observation that urea is a powerful active-site inhibitor of amidase, which catalyzes the hydrolysis of amides such as acetamide to produce ammonia and the corresponding organic acid. Cell-free extract from Pseudomonas aeruginosa was the source of amidase (acylamide hydrolase, EC 3.5.1.4) which was immobilized on a polyethersulfone membrane in the presence of glutaraldehyde; anion-selective electrode for ammonium ions was used for biosensor development. Analysis of variance was used for optimization of the biosensorresponse and showed that 30 mu L of cell-free extract containing 7.47 mg protein mL(-1), 2 mu L of glutaraldehyde (5%, v/v) and 10 mu L of gelatin (15%, w/v) exhibited the highest response. Optimization of other parameters showed that pH 7.2 and 30 min incubation time were optimum for incubation ofmembranes in urea. The biosensor exhibited a linear response in the range of 4.0-10.0 mu M urea, a detection limit of 2.0 mu M for urea, a response timeof 20 s, a sensitivity of 58.245 % per mu M urea and a storage stability of over 4 months. It was successfully used for quantification of urea in samples such as wine and milk; recovery experiments were carried out which revealed an average substrate recovery of 94.9%. The urea analogs hydroxyurea, methylurea and thiourea inhibited amidase activity by about 90%, 10% and 0%, respectively, compared with urea inhibition

A goal programming approach for balancing diet costs and feed water use under different environmental conditions.

Water is essential in livestock production systems. In typical dairy production systems, 90% of the total water used by a dairy farm is attributed to feed production. Theoretically, ration manipulation is a method to potentially reduce the irrigation water needed for feed crops without dramatically increasing diet costs. However, published quantitative studies on the relationship between feed production and water use that are integrated with linear programming models are scarce. The overall objective of this study was to develop an optimization framework that could achieve a balance between minimization of dietary costs and dietary irrigation water usage, and that could be used as a framework for future research and models for various livestock production systems. Weighted goal programming models were developed to minimize the dietary costs and irrigation water usage for a hypothetical cow under 8 different environmental scenarios. The environmental conditions used a 2 × 2 × 2 factorial design, including 2 atmospheric CO2 concentrations (400 and 550 ppm), 2 water years (dry and wet), and 2 irrigation methods (furrow and drip). A systematic weighting scheme was used to model the trade-off between minimizing diet cost and minimizing irrigation water use for feedstuffs. Each environmental condition generated a set of distinct diets, which each met the same nutrient requirements of the hypothetical cow but had a different water usage when the weighting scheme was changed from weighting minimum diet costs to minimum irrigation water usage. For water resource planning in areas of dairy production, this set of unique solutions provides the decision maker with different feeding options according to diet cost, water usage, and available feeds. As water was more constrained, dietary dry matter intake increased, concentrations of neutral detergent fiber, ether extract, and energy decreased, and the concentration of lignin increased because less nutritive but more water-saving feedstuffs were included in the diet. Mitigation costs of water usage were calculated from goal programming results and indicated that the potential value of water under water-limited conditions (e.g., in a drought region) was higher than that under water-sufficient conditions. However, a smaller increase in feed costs can initially significantly reduce water usage compared with that of a least-cost diet, which implies that the reduction of water usage through ration manipulation might be possible. This model serves as a framework for the study of irrigation water usage in dairy production and other livestock production systems and for decision-making processes involved in water resources planning in the broader area of animal production

Genetic variability of milk fatty acids.

The milk fatty acid (FA) profile is far from the optimal fat composition in regards to human health. The natural sources of variation, such as feeding or genetics, could be used to increase the concentrations of unsaturated fatty acids. The impact of feeding is well described. However, genetic effects on the milk FA composition begin to be extensively studied. This paper summarizes the available information about the genetic variability of FAs. The greatest breed differences in FA composition are observed between Holstein and Jersey milk. Milk fat of the latter breed contains higher concentrations of saturated FAs, especially short-chain FAs. The variation of the delta-9 desaturase activity estimated from specific FA ratios could explain partly these breed differences. The choice of a specific breed seems to be a possibility to improve the nutritional quality of milk fat. Generally, the proportions of FAs in milk are more heritable than the proportions of these same FAs in fat. Heritability estimates range from 0.00 to 0.54. The presence of some single nucleotide polymorphisms could explain partly the observed individual genetic variability. The polymorphisms detected on SCD1 and DGAT1 genes influence the milk FA composition. The SCD1 V allele increases the unsaturation of C16 and C18. The DGAT1 A allele is related to the unsaturation of C18. So, a combination of the molecular and quantitative approaches should be used to develop tools helping farmers in the selection of their animals to improve the nutritional quality of the produced milk fat