Accurate assessment of nutrient bioavailability is critical for achieving an optimal balance between sufficient and excess for major feed components such as protein sources. Optimizing feed protein sources for farm animal amino acid (AA) requirements is difficult to achieve given the variations in protein quality. Feeding excess protein to meet AA requirements contributes to excess nitrogen (N) environmental pollution. To avoid productivity losses from an improper AA balance, feeds can be supplemented with pure AA to reduce animal N excretion. This requires AA bioavailability assessment by animal bioassays prior to supplementation. However in addition to the time commitment and costs, activism interests are beginning to restrict routine animal tests. Ideally the animal feed industry needs alternative rapid methods for quantifying AA availability during feed processing. Rapid assays would allow animal nutritionists to adjust AA addition after assessing basal diet AA bioavailability. In vitro microbial bioassays for AA and other nutrients have been examined as a rapid alternative for a number of years. Such assays have the advantages of biological similarity to animal responses while retaining the flexibility and reproducibility capabilities of a conventional chemical test. Although several microorganisms have been examined, Escherichia coli has become the assay organism of choice because it is well studied, has simple growth requirements, and genetic modification is relatively easy. Given the molecular techniques currently available E. coli can easily be genetically engineered to provide an array of rapid whole cell AA biosensors. General application of this technology opens the door for more precise formulation at the feed mill and avoidance of unnecessary supplementation that result in animal production generated environmental problems.
[1]
H. Garreau,et al.
Survival analysis in two lines of rabbits selected for reproductive traits.
,
2006,
Journal of animal science.
[2]
M. Baselga,et al.
Analysis of rabbit doe longevity using a semiparametric log-Normal animal frailty model with time-dependent covariates
,
2006,
Genetics Selection Evolution.
[3]
M. A. Silvestre,et al.
Analysis of factors influencing longevity of rabbit does
,
2004
.
[4]
P. Visscher,et al.
Heritability, reliability of genetic evaluations and response to selection in proportional hazard models.
,
2002,
Journal of dairy science.