RESUMEN
This study presents "mouse tissue glycome atlas" representing the profiles of major N-glycans of mouse glycoproteins that may define their essential functions in the surface glycocalyx of mouse organs/tissues and serum-derived extracellular vesicles (exosomes). Cell surface glycocalyx composed of a variety of N-glycans attached covalently to the membrane proteins, notably characteristic "N-glycosylation patterns" of the glycocalyx, plays a critical role for the regulation of cell differentiation, cell adhesion, homeostatic immune response, and biodistribution of secreted exosomes. Given that the integrity of cell surface glycocalyx correlates significantly with maintenance of the cellular morphology and homeostatic immune functions, dynamic alterations of N-glycosylation patterns in the normal glycocalyx caused by cellular abnormalities may serve as highly sensitive and promising biomarkers. Although it is believed that inter-organs variations in N-glycosylation patterns exist, information of the glycan diversity in mouse organs/tissues remains to be elusive. Here we communicate for the first-time N-glycosylation patterns of 16 mouse organs/tissues, serum, and serum-derived exosomes of Slc:ddY mice using an established solid-phase glycoblotting platform for the rapid, easy, and high throughput MALDI-TOFMS-based quantitative glycomics. The present results elicited occurrence of the organ/tissue-characteristic N-glycosylation patterns that can be discriminated to each other. Basic machine learning analysis using this N-glycome dataset enabled classification between 16 mouse organs/tissues with the highest F1 score (69.7-100%) when neural network algorithm was used. A preliminary examination demonstrated that machine learning analysis of mouse lung N-glycome dataset by random forest algorithm allows for the discrimination of lungs among the different mouse strains such as the outbred mouse Slc:ddY, inbred mouse DBA/2Crslc, and systemic lupus erythematosus model mouse MRL-lpr/lpr with the highest F1 score (74.5-83.8%). Our results strongly implicate importance of "human organ/tissue glycome atlas" for understanding the crucial and diversified roles of glycocalyx determined by the organ/tissue-characteristic N-glycosylation patterns and the discovery research for N-glycome-based disease-specific biomarkers and therapeutic targets.
Asunto(s)
Glicoproteínas , Polisacáridos , Animales , Ratones , Biomarcadores , Proteínas de la Membrana , Ratones Endogámicos DBA , Ratones Endogámicos MRL lpr , Distribución TisularRESUMEN
Clusterin is a heavily glycosylated protein that is upregulated in various cancer and neurological diseases. The findings by the Hancock and Iliopoulos group that levels of the tryptic glycopeptide derived from plasma clusterin, 372Leu-Ala-Asn-Leu-Thr-Gln-Gly-Glu-Asp-Gln-Tyr-Tyr-Leu-Arg385 with a biantennary disialyl N-glycan (A2G2S2 or FA2G2S2) at Asn374 differed significantly prior to and after curative nephrectomy for clear cell renal cell carcinoma (RCC) patients motivated us to verify the feasibility of this glycopeptide as a novel biomarker of RCC. To determine the precise N-glycan structure attached to Asn374, whether A2G2S2 is composed of the Neu5Acα2,3Gal or/and the Neu5Acα2,6Gal moiety, we synthesized key glycopeptides having one of the two putative isomers. Selective reaction monitoring assay using synthetic glycopeptides as calibration standards allowed "top-down glycopeptidomics" for the absolute quantitation of targeted label-free glycopeptides in a range from 313.3 to 697.5 nM in the complex tryptic digests derived from serum samples of RCC patients and healthy controls. Our results provided evidence that the Asn374 residue of human clusterin is modified dominantly with the Neu5Acα2,6Gal structure and the levels of clusterin bearing an A2G2S2 with homo Neu5Acα2,6Gal terminals at Asn374 decrease significantly in RCC patients as compared with healthy controls. The present study elicits that a new strategy integrating the bottom-up glycoproteomics with top-down glycopeptidomics using structure-defined synthetic glycopeptides enables the confident identification and quantitation of the glycopeptide targets pre-determined by the existing methods for intact glycopeptide profiling.
RESUMEN
Despite emerging importance of tumor cells-derived exosomes in cancer metastasis, the heterogeneity of exosome populations has largely hampered systemic characterization of their molecular composition, biogenesis, and functions. This study communicates a novel method for predicting and targeting pre-metastatic sites based on an exosome model "fluorescent cancer glyconanosomes" displaying N-glycans of cultured tumor cells. Glycoblotting by antiadhesive quantum dots provides a nice tool to shed light on the pivotal functions of the glycocalyx reconstructed from four cancer cell types without bias due to other compositions of exosomes. In vivo imaging revealed that circulation, clearance, and organotropic biodistribution of cancer glyconanosomes in mice depend strongly on cancer cell-type-specific N-glycosylation patterns, the compositions of key glycotypes, particularly dominant abundances of high mannose-type N-glycans and the position-specific sialylation. Notably, organ biodistribution of cancer glyconanosomes is reproducible artificially by mimicking cancer cell-type-specific N-glycosylation patterns, demonstrating that nanosomal glycoblotting method serves as promising tools for predicting and targeting pre-metastatic sites determined by the glycocalyx of extracellular vesicles disseminated from the primary cancer site.