(191e) Linking Metabolizable Energy to Chemical Oxygen Demand | AIChE

(191e) Linking Metabolizable Energy to Chemical Oxygen Demand


Davis, T. L. - Presenter, Arizona State University
Rittmann, B., Arizona State University
Marcus, A. K., Arizona State University
Dirks, B. E., Arizona State University
Krajmalnik-Brown, R., Arizona State University
Smith, S. R., Translational Research Institute
Corbin, K. D., Translational Research Institute
A human and the human’s intestinal microbiome interact in complex ways that influence human health. Interactions involving metabolism are very pronounced and have captured much attention. To deepen understanding of human-microbe metabolic interactions, research experts in human metabolism, microbial metabolism and ecology, and engineering are joining forces. For historical and topical reasons, these disciplines use different metrics to quantify mass and energy. The metabolizable energy (ME, units: kcal) of food is a primary metric for human nutrition and metabolism. ME is the net energy within the food that is available to humans after digestion; it is equivalent to the gross energy intake minus body wastes (i.e., urine, feces, gases, and shedding). Microbial ecologists and environmental engineers track the energy embodied in electron equivalents using the chemical oxygen demand (COD). COD is the amount of oxygen required to oxidize organic matter, and it is related to electron equivalents via 8 g COD/ e- eq. In order to develop a consistent means to link energy and electron balances, which is essential for integrating the roles of human and microbial metabolism, an essential first step is to link ME and COD.

The purpose of this study was to develop a correlation between COD and energy values in common food items. We developed a framework to convert between COD and ME in four steps. First, we gathered food items representing the three macronutrients -- carbohydrates, protein, and fat – and classified them according to their complexity: monomers, polymers, or complex ingredients. Using the carbohydrate macronutrient as an example, glucose is classified as a monomer, resistant starch as a polymer, and maple syrup as a complex ingredient. Second, we developed a chemical formula of each food item to calculate the theoretical COD. The monomers and polymers have known formulas. We calculated the complex ingredients’ formulas from nutrient data on the USDA food database: The macronutrient composition of the food items listed in the database can be used to determine the molar ratio of carbon, hydrogen, oxygen, and nitrogen atoms to derive a molecular formula. Third, we compared the theoretical COD with the experimental COD values measured using a commercial COD measurement kit. For the complex ingredients, the measured COD was used to confirm accuracy of the developed molecular formula. Fourth, the ME of the food was calculated using the Atwater equations. The result of this framework is a value for the ME and the COD for each of the food items. This methodology was completed for representative food items. The results were used to establish a correlation between ME and COD values.

Our results show that the developed molecular formulas accurately predicted the measured COD. For example, the theoretical and measured COD of egg whites agreed within ±1%. When the COD values were compared with the energy values, the best fit was linear. We observed an R2 value calculated using the Pearson correlation of 0.992, a slope of 3.4 kcal/gCOD, and an intercept of 0.15 kcal/g. These results demonstrate that accurate conversion between ME and COD is possible for many food items. By providing a rubric for linking energy (kcal) measurements with electron equivalents (COD), we establish a framework to connect the bioenergetic interactions of humans and their microbiomes. This is an essential first step towards integrating microbial and human mathematical models and interpreting clinical results.