Aditya Bhagwat

Kinetic modeling of a bi-enzymatic system for efficient conversion of lactose to lactobionic acid.

A model has been developed to describe the interaction between two enzymes and an intermediary redox mediator. In this bi‐enzymatic process, the enzyme cellobiose dehydrogenase oxidizes lactose at the C‐1 position of the reducing sugar moiety to lactobionolactone, which spontaneously hydrolyzes to lactobionic acid. 2,2′‐Azino‐bis(3‐ethylbenzothiazoline‐6‐sulfonic acid) diammonium salt is used as electron acceptor and is continuously regenerated by laccase. Oxygen is the terminal electron acceptor and is fully reduced to water by laccase, a copper‐containing oxidase. Oxygen is added to the system by means of bubble‐free oxygenation. Using the model, the productivity of the process is investigated by simultaneous solution of the rate equations for varying enzyme quantities and redox mediator concentrations, solved with the aid of a numerical solution. The isocharts developed in this work provide an easy‐to‐use graphical tool to determine optimal process conditions. The model allows the optimization of the employed activities of the two enzymes and the redox mediator concentration for a given overall oxygen mass transfer coefficient by using the isocharts. Model predictions are well in agreement with the experimental data. Biotechnol. Bioeng. 2009;102: 1475–1482.

Prediction of ruminal volatile fatty acid proportions of lactating dairy cows based on milk odd- and branched-chain fatty acid profiles: New models, better predictions

The volatile fatty acids (VFA) produced in the rumen and the proportions in which they are produced are important determinants of a ruminants metabolism, but their monitoring requires rumen-fistulated animals, which is not feasible under practical conditions or in experimental setups at herd level. An alternative approach was suggested earlier, consisting of predicting the VFA proportions from measured odd- and branched-chain fatty acid concentrations in the milk with a linear model. Here, we have improved this strategy through the development and application of 2 new model structures: the quadratic model, containing quadratic terms and interactions, and the rational model, consisting of a ratio of linear expressions. Both were found to improve prediction accuracy significantly compared with the linear model. Although the quadratic model achieved the best prediction accuracy, the rational model has the interesting property that it takes the dependence of the 3 predicted VFA into account and guarantees that the 3 proportions add up to 1. Adding a study effect to correct for a possible study bias in the multi-study data improved prediction substantially for all 3 methods. Our results demonstrate the potential of using milk odd- and branched-chain fatty acid concentrations to predict rumen VFA proportions.