Breast milk is the ideal nutrition for term infants but must be supplemented to provide adequate growth for most premature infants. Human milk oligosaccharides (HMOs) are remarkably abundant and diverse in breast milk and yet provide no nutritive value to the infant. HMOs appear to have at least two major functions: prebiotic activity (stimulation of the growth of commensal bacteria in the gut) and protection against pathogens. Investigations of HMOs in milk from women delivering preterm have been limited. We present the first detailed mass spectrometric analysis of the fucosylation and sialylation in HMOs in serial specimens of milk from fifteen women delivering preterm and seven women delivering at term using nano-high performance liquid chromatography chip/time-of-flight mass spectrometry. A mixed-effects model with Levene’s test was used for the statistical analyses. We find that lacto-N-tetraose, a core HMO, is both more abundant and more highly variable in the milk of women delivering preterm. Furthermore, fucosylation in preterm milk is not as well regulated as in term milk, resulting in higher within and between mother variation in women delivering preterm vs. term. Of particular clinical interest, the α1,2-linked fucosylated oligosaccharide 2′-fucosyllactose, an indicator of secretor status, is not consistently present across lactation of several mothers that delivered preterm. The immaturity of HMO production does not appear to resolve over the time of lactation and may have relevance to the susceptibility of premature infants to necrotizing enterocolitis, late onset sepsis, and related neurodevelopmental impairments.

Background Human milk oligosaccharides (HMOs) shape the intestinal microbiota in term infants. In premature infants, alterations in the intestinal microbiota (dysbiosis) are associated with risk of necrotizing enterocolitis and sepsis and the influence of HMOs on the microbiota is unclear. Methods Milk, urine, and stool specimens from 14 mother-premature infant dyads were investigated by mass spectrometry for HMO composition. The stools were analyzed by next-generation sequencing (NGS) to complement a previous analysis. Results Percentages of fucosylated and sialylated HMOs were highly variable between individuals but similar in urine, feces and milk within dyads. Differences in urine and fecal HMO composition suggest variability in absorption. Secretor status of the mother correlated with the urine and fecal content of specific HMO structures. Trends toward higher levels of Proteobacteria and lower levels of Firmicutes, were noted in premature infants of non-secretor mothers. Specific HMO structures in the milk, urine and feces were associated with alterations in fecal Proteobacteria and Firmicutes. Conclusion HMOs may influence the intestinal microbiota in premature infants. Specific HMOs, for example those associated with secretor mothers, may have a protective effect by decreasing pathogens associated with sepsis and necrotizing enterocolitis while other HMOs may increase dysbiosis in this population.

An extensive mass spectrometry analysis of the human milk peptidome has revealed almost 700 endogenous peptides from 30 different proteins. Two in-house computational tools were created and used to visualize and interpret the data through both alignment of the peptide quasi-molecular ion intensities and estimation of the differential enzyme participation. These results reveal that the endogenous proteolytic activity in the mammary gland is remarkably specific and well conserved. Certain proteins-not necessarily the most abundant ones-are digested by the proteases present in milk, yielding endogenous peptides from selected regions. Our results strongly suggest that factors such as the presence of specific proteases, the position and concentration of cleavage sites, and, more important, the intrinsic disorder of segments of the protein drive this proteolytic specificity in the mammary gland. As a consequence of this selective hydrolysis, proteins that typically need to be cleaved at specific positions in order to exert their activity are properly digested, and bioactive peptides encoded in certain protein sequences are released. Proteins that must remain intact in order to maintain their activity in the mammary gland or in the neonatal gastrointestinal tract are unaffected by the hydrolytic environment present in milk. These results provide insight into the intrinsic structural mechanisms that facilitate the selectivity of the endogenous milk protease activity and might be useful to those studying the peptidomes of other biofluids. Molecular &

Aberrant glycosylation has been observed for decades in essentially all types of cancer, and is now well established as an indicator of carcinogenesis. Mining the glycome for biomarkers, however, requires analytical methods that can rapidly separate, identify, and quantify isomeric glycans. We have developed a rapid-throughput method for chromatographic glycan profiling using microfluidic chip-based nanoflow liquid chromatography (nano-LC)/mass spectrometry. To demonstrate the utility of this method, we analyzed and compared serum samples from epithelial ovarian cancer cases (n = 46) and healthy control individuals (n = 48). Over 250 N-linked glycan compound peaks with over 100 distinct N-linked glycan compositions were identified. Statistical testing identified 26 potential glycan biomarkers based on both compositional and structure-specific analyses. Using these results, an optimized model was created incorporating the combined abundances of seven potential glycan biomarkers. The receiver operating characteristic (ROC) curve of this optimized model had an area under the curve (AUC) of 0.96, indicating robust discrimination between cancer cases and healthy controls. Rapid-throughput chromatographic glycan profiling was found to be an effective platform for structure-specific biomarker discovery.

Human serum glycomics is a promising method for finding cancer biomarkers but often lacks the tools for streamlined data analysis. The Glycolyzer software incorporates a suite of analytic tools capable of identifying informative glycan peaks out of raw mass spectrometry data. As a demonstration of its utility, the program was used to identify putative biomarkers for epithelial ovarian cancer from a human serum sample set. A randomized, blocked and blinded experimental design was used on a discovery set consisting of 46 cases and 48 controls. Retrosynthetic glycan libraries were used for data analysis and several significant candidate glycan biomarkers were discovered via hypothesis testing. The significant glycans were attributed to a glycan family based on glycan composition relationships and incorporated into a linear classifier motif test. The motif test was then applied to the discovery set to evaluate the disease state discrimination performance. The test provided strongly predictive results based on receiver operator characteristic curve analysis. The area under the receiver operator characteristic curve was 0.93. Using the Glycolyzer software, we were able to identify a set of glycan biomarkers that highly discriminate between cases and controls, and are ready to be formally validated in subsequent studies.