Impact of pasteurization on the self-assembly of human milk lipids during digestion.

Human milk is critical for the survival and development of infants. This source of nutrition contains components that protect against infections while stimulating immune maturation. In cases where the mother's own milk is unavailable, pasteurized donor milk is the preferred option. Although pasteurization has been shown to have minimal impact on the lipid and FA composition before digestion, no correlation has been made between the impact of pasteurization on the FFA composition and the self-assembly of lipids during digestion, which could act as delivery mechanisms for poorly water-soluble components. Pooled nonpasteurized and pasteurized human milk from a single donor was used in this study. The evolving FFA composition during digestion was determined using GC coupled to a flame ionization detector. In vitro digestion coupled to small-angle X-ray scattering was utilized to investigate the influence of different calcium levels, fat content, and the presence of bile salts on the extent of digestion and structural behavior of human milk lipids. Almost complete digestion was achieved when bile salts were added to the systems containing high calcium to milk fat ratio, with similar structural behavior of lipids during digestion of both types of human milk being apparent. In contrast, differences in the colloidal structures were formed during digestion in the absence of bile salt because of a greater amount of FFAs being released from the nonpasteurized than pasteurized milks. This difference in FFAs released from both types of human milk could result in varying nutritional implications for infants.

TAILOR-MS, a Python Package that Deciphers Complex Triacylglycerol Fatty Acyl Structures: Applications for Bovine Milk and Infant Formulas.

Liquid chromatography tandem mass spectrometry (LC/MS) and other mass spectrometric technologies have been widely applied for triacylglycerol profiling. One challenge for targeted identification of fatty acyl moieties that constitute triacylglycerol species in biological samples is the numerous combinations of 3 fatty acyl groups that can form a triacylglycerol molecule. Manual determination of triacylglycerol structures based on peak intensities and retention time can be highly inefficient and error-prone. To resolve this, we have developed TAILOR-MS, a Python (programming language) package that aims at assisting: (1) the generation of targeted LC/MS methods for triacylglycerol detection and (2) automating triacylglycerol structural determination and prediction. To assess the performance of TAILOR-MS, we conducted LC/MS triacylglycerol profiling of bovine milk and two infant formulas. Our results confirmed dissimilarities between bovine milk and infant formula triacylglycerol composition. Furthermore, we identified 247 triacylglycerol species and predicted the possible existence of another 317 in the bovine milk sample, representing one of the most comprehensive reports on the triacylglycerol composition of bovine milk thus far. Likewise, we presented here a complete infant formula triacylglycerol profile and reported >200 triacylglycerol species. TAILOR-MS dramatically shortened the time required for triacylglycerol structural identification from hours to seconds and performed decent structural predictions in the absence of some triacylglycerol constituent peaks. Taken together, TAILOR-MS is a valuable tool that can greatly save time and improve accuracy for targeted LC/MS triacylglycerol profiling.