Nucleotide sugars are the donor substrates of various glycosyltransferases, and an important building block in
N- and
O-glycan biosynthesis. Their intercellular concentrations are regulated by cellular metabolic states including diseases such as cancer and diabetes. To investigate the fate of UDP-GlcNAc, we developed a tracing method for UDP-GlcNAc synthesis and use, and GlcNAc utilization using
13C
6-glucose and
13C
2-glucosamine, respectively, followed by the analysis of mass isotopomers using LC-MS.Metabolic labeling of cultured cells with
13C
6-glucose and the analysis of isotopomers of UDP-HexNAc (UDP-GlcNAc plus UDP-GalNAc) and CMP-NeuAc revealed the relative contributions of metabolic pathways leading to UDP-GlcNAc synthesis and use. In pancreatic insulinoma cells, the labeling efficiency of a
13C
6-glucose motif in CMP-NeuAc was lower compared with that in hepatoma cells.Using
13C
2-glucosamine, the diversity of the labeling efficiency was observed in each sugar residue of
N- and
O-glycans on the basis of isotopomer analysis. In the insulinoma cells, the low labeling efficiencies were found for sialic acids as well as tri- and tetra-sialo
N-glycans, whereas asialo
N-glycans were found to be abundant. Essentially no significant difference in secreted hyaluronic acids was found among hepatoma and insulinoma cell lines. This indicates that metabolic flows are responsible for the low sialylation in the insulinoma cells. Our strategy should be useful for systematically tracing each stage of cellular GlcNAc metabolism.Protein glycosylation, which is the most abundant post-translational modification, has important roles in many biological processes by modulating conformation and stability, whereas its dysregulation is associated with various diseases such as diabetes and cancer (
1,
2). Glycosylation is regulated by various factors including glucose metabolism, the availability and localization of nucleotide sugars, and the expression and localization of glycosyltransferases (
3,
4). Thus, ideally all of these components should be considered when detecting changes in a dynamic fashion; namely, it is necessary not only to take a snapshot but also to make movies of the dynamic changes in glycan metabolism.Glucose is used by living cells as an energy source via the glycolytic pathway as well as a carbon source for various metabolites including nucleotide sugars (
e.g. UDP-GlcNAc and CMP-NeuAc). These nucleotide sugars are transported into the Golgi apparatus, and added to various glycans on proteins. UDP-GlcNAc is the donor substrate for
N-acetylglucosaminyl (GlcNAc)
1 transferases; alternatively, it is used in the cytosol for
O-GlcNAc modification (
i.e. O-GlcNAcylation) of intracellular proteins (
5). The UDP-GlcNAc synthetic pathway is complex as it is a converging point of glucose, nucleotide, fatty acid and amino acid metabolic pathways. Thus, the metabolic flow of glucose modulates the branching patterns of
N-glycans via UDP-GlcNAc concentrations because many of the key GlcNAc transferases that determine the branching patterns have widely different
Km values for UDP-GlcNAc ranging from 0.04 m
m to 11 m
m (
6,
7). Indeed, it was demonstrated that the branching formation of
N-glycans in T cells is stimulated by the supply from the hexosamine pathway, whereby it regulates autoimmune reactions promoted by T cells (
8).UDP-GlcNAc is also used for the synthesis of CMP-NeuAc, the donor substrate for sialyltransferases (
9). The CMP-NeuAc concentration is controlled by the feedback inhibition of UDP-GlcNAc epimerase/ManNAc kinase by the final product CMP-NeuAc, and hence a high CMP-NeuAc level reduces metabolic flow in CMP-NeuAc
de novo synthesis (
10). However, there is still only limited information about how the levels of nucleotide sugars dynamically change in response to the environmental cues, and how such changes are reflected in the glycosylation of proteins.Stable isotope labeling is a promising approach to quantify metabolic changes in response to external cues (
11,
12). For example, the use of nuclear magnetic resonance to obtain isotopomer signals of metabolically labeled molecules has been applied to trace the flux in glycolysis and fatty acid metabolism (
13). An approach based on the mass isotopomers of labeled metabolites with
13C
6-glucose has been developed to monitor the UDP-GlcNAc synthetic pathway (
13–
15). The method based on the labeling ratio of each metabolite related to UDP-GlcNAc synthesis has clarified the contribution of each metabolic pathway (
14). Moseley reported a novel deconvolution method for modeling UDP-GlcNAc mass isotopomers (
15).Previous studies into the use of nucleotide sugars in glycosylation have relied on the specific detection of metabolically radiolabeled glycans (
16). It is possible not only to deduce the glycan structures but also to trace their relative contributions to glycan synthesis without MS. On the other hand, mass isotopomer analysis of glycans labeled with stable isotope provides the ratios of labeled
versus unlabeled molecules from MS spectra and structural details of the glycans. However, there are only a limited number of publications reporting the application of stable isotope labeling of glycans for monitoring the dynamics of glycans (
17). To date, there have been no reports describing a systematic method for tracing cellular GlcNAc biosynthesis and use based on mass isotopomer analysis.The aim of this study was to extend our knowledge of the synthesis and metabolism of UDP-GlcNAc as well as its use in the synthesis of CMP-NeuAc,
N- and
O-glycans. We recently developed a conventional HPLC method for simultaneous determination of nucleotide sugars including unstable CMP-NeuAc (
18). We first established an LC-MS method for isotopomer analysis of
13C
6-glucose labeled nucleotide sugars for tracing UDP-GlcNAc metabolism from synthesis to use, because previous methods were not suitable for estimating UDP-GlcNAc use in CMP-NeuAc
de novo synthesis (
15). We also established a method for isotopomer analysis of labeled
N- and
O-glycan to monitor the metabolic flow of hexosamine into glycans. Using these two methods, we demonstrated the differences in the use of hexosamines between hepatoma and pancreatic insulinoma cell lines. Our approach may be useful for identifying a metabolic “bottleneck” that governs the turnover speed and patterns of cellular glycosylation, which may be relevant for various applications including glycoprotein engineering and discovery of disease biomarkers.
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