A sulfur amino acid deficiency changes the amino acid composition of body protein in piglets

Experiments carried out to determine the amino acid requirement in growing animals are often based on the premise that the amino acid composition of body protein is constant. However, there are indications that this assumption may not be correct. The objective of this study was to test the effect of feeding piglets a diet deficient or not in total sulfur amino acids (TSAA; Met + Cys) on nitrogen retention and amino acid composition of proteins in different body compartments. Six blocks of three pigs each were used in a combined comparative slaughter and nitrogen balance study. One piglet in each block was slaughtered at 42 days of age, whereas the other piglets received a diet deficient or not in TSAA for 19 days and were slaughtered thereafter. Two diets were formulated to provide either 0.20% Met and 0.45% TSAA (on a standardized ileal digestible basis) or 0.46% Met and 0.70% TSAA. Diets were offered approximately 25% below ad libitum intake. At slaughter, the whole animal was divided into carcass, blood, intestines, liver, and the combined head, tail, feet and other organs (HFTO), which were analyzed for nitrogen and amino acid contents. Samples of the longissimus muscle (LM) were analyzed for myosin heavy chain (MyHC) and actin contents. Nitrogen retention was 20% lower in piglets receiving the TSAA-deficient diet (P < 0.01). In these piglets, the nitrogen content in tissue gain was lower in the empty body, carcass, LM and blood (P < 0.05) or tended to be lower in HFTO (P < 0.10), but was not different in the intestines and liver. The Met content in retained protein was lower in the empty body, LM and blood (P < 0.05), and tended to be lower in the carcass (P < 0.10). The Cys content was lower in LM, but higher in blood of piglets receiving the TSAA-deficient diet (P < 0.05). Skeletal muscle appeared to be affected most by the TSAA deficiency. In LM, the Met content in retained protein was reduced by 12% and total Met retention by more than 60%. The MyHC and actin contents in LM were not affected by the TSAA content of the diet. These results show that a deficient TSAA supply affects the amino acid composition of different body proteins. This questions the use of a constant ideal amino acid profile to express dietary amino acid requirements, but also illustrates the plasticity of the animal to cope with nutritional challenges.     

Amino acid composition and C-terminal residues of algal biliproteins

1. R-phycoerythrin from Ceramium rubrum and C-phycocyanin from Nostoc muscorum have been obtained in purified form by fractional crystallization, followed by chromatography and gel-filtration. 2. The amino acid composition of both chromoproteins was determined; 85% of the total weight of both was recovered as amino acids. 3. Alanine was identified as the only C-terminal amino acid of R-phycoerythrin, each molecule of which contained about 12 terminal groups. 4. Serine was identified as the only C-terminal group of C-phycocyanin.     

Predicting the cofactors of oxidoreductases based on amino acid composition distribution and Chou's amphiphilic pseudo-amino acid composition

Predicting the cofactors of oxidoreductases plays an important role in inferring their catalytic mechanism. Feature extraction is a critical part in the prediction systems, requiring raw sequence data to be transformed into appropriate numerical feature vectors while minimizing information loss. In this paper, we present an amino acid composition distribution method for extracting useful features from primary sequence, and the k-nearest neighbor was used as the classifier. The overall prediction accuracy evaluated by the 10-fold cross-validation reached 90.74%. Comparing our method with other eight feature extraction methods, the improvement of the overall prediction accuracy ranged from 3.49% to 15.74%. Our experimental results confirm that the method we proposed is very useful and may be used for other bioinformatical predictions. Interestingly, when features extracted by our method and Chou's amphiphilic pseudo-amino acid composition were combined, the overall accuracy could reach 92.53%.     

A study on the correlation of G-protein-coupled receptor types with amino acid composition

G-protein-coupled receptors have become a target in utilizing bioinformatics and genomics technology to facilitate drug discovery for psychiatric diseases. In this study the covariant-discriminant algorithm [Chou and Elrod (1999) Protein Eng., 12, 107-118] has been used to analyze the correlation between the types of G-protein-coupled receptors and the amino acid composition. It has been found that different types of G-protein-coupled receptors are quite closely correlated with the amino acid composition, implying that the types of G-protein-coupled receptors are predictable to a considerably accurate extent if a good training data set can be established for that purpose. The method derived here can be also used to do preliminary classification of orphan G-protein-coupled receptors. This will significantly expedite the process of identifying proper G-protein-coupled receptors for drug discovery.