Dallas, D. C., A. Guerrero, N. Khaldi, P. A. Castillo, W. F. Martin, J. T. Smilowitz, C. L. Bevins, D. Barile, J. B. German and C. B. Lebrilla (2013). “Extensive in vivo Human Milk Peptidomics Reveals Specific Proteolysis Yielding Protective Antimicrobial Peptides.” J Proteome Res 12(5): 2295-2304.
Milk is traditionally considered an ideal source of the basic elemental nutrients required by infants. More detailed examination is revealing that milk represents a more functional ensemble of components with benefits to both infants and mothers. A comprehensive peptidomics method was developed and used to analyze human milk yielding an extensive array of protein products present in the fluid. Over 300 milk peptides were identified originating from major and many minor protein components of milk. As expected, the majority of peptides derived from beta-casein, however no peptide fragments from the major milk proteins lactoferrin, alpha-lactalbumin, and secretory immunoglobulin A were identified. Proteolysis in the mammary gland is selective-released peptides were drawn only from specific proteins and typically from only select parts of the parent sequence. A large number of the peptides showed significant sequence overlap with peptides with known antimicrobial or immunomodulatory functions. Antibacterial assays showed the milk peptide mixtures inhibited the growth of Escherichia coli and Staphylococcus aureus . The predigestion of milk proteins and the consequent release of antibacterial peptides may provide a selective advantage through evolution by protecting both the mother’s mammary gland and her nursing offspring from infection.

Ruhaak, L. R., U. T. Nguyen, C. Stroble, S. L. Taylor, A. Taguchi, S. M. Hanash, C. B. Lebrilla, K. Kim and S. Miyamoto (2013). “Enrichment strategies in glycomics based lung cancer biomarker development.” Proteomics Clin Appl.
PURPOSE: There is a need to identify better glycan biomarkers for diagnosis, early detection and treatment monitoring in lung cancer using biofluids such as blood. Biofluids are complex mixtures of proteins dominated by a few high abundance proteins that may not have specificity for lung cancer. Therefore two methods for protein enrichment were evaluated; affinity capturing of IgG and enrichment of medium abundance proteins, thus allowing us to determine which method yields the best candidate glycan biomarkers for lung cancer. EXPERIMENTAL DESIGN: N-glycans isolated from plasma samples from 20 cases of lung adenocarcinoma and 20 matched controls were analyzed using nLC-PGC-chip-TOF-MS. N-glycan profiles were obtained for five different fractions: total plasma, isolated IgG, IgG depleted plasma, and the bound and flow-through fractions of protein enrichment. RESULTS: Four glycans differed significantly (FDR<0.05) between cases and controls in whole unfractionated plasma, while four other glycans differed significantly by cancer status in the IgG fraction. No significant glycan differences were observed in the other fractions. CONCLUSIONS AND CLINICAL RELEVANCE: These results confirm that the N-glycan profile in plasma of lung cancer patients is different from healthy controls and appears to be dominated by alterations in relatively abundant proteins. This article is protected by copyright. All rights reserved.

Strum, J. S., C. C. Nwosu, S. Hua, S. R. Kronewitter, R. R. Seipert, R. J. Bachelor, H. J. An and C. B. Lebrilla (2013). “Automated Assignments of N- and O-Site Specific Glycosylation with Extensive Glycan Heterogeneity of Glycoprotein Mixtures.” Anal Chem.
Site-specific glycosylation (SSG) of glycoproteins remains a considerable challenge and limits further progress in the areas of proteomics and glycomics. Effective methods require new approaches in sample preparation, detection, and data analysis. While the field has advanced in sample preparation and detection, automated data analysis remains an important goal. A new bioinformatics approach implemented in software called GP Finder automatically distinguishes correct assignments from random matches and complements experimental techniques that are optimal for glycopeptides, including nonspecific proteolysis and high mass resolution liquid chromatography/tandem mass spectrometry (LC/MS/MS). SSG for multiple N- and O-glycosylation sites, including extensive glycan heterogeneity, was annotated for single proteins and protein mixtures with a 5% false-discovery rate, generating hundreds of nonrandom glycopeptide matches and demonstrating the proof-of-concept for a self-consistency scoring algorithm shown to be compliant with the target-decoy approach (TDA). The approach was further applied to a mixture of N-glycoproteins from unprocessed human milk and O-glycoproteins from very-low-density-lipoprotein (vLDL) particles.