Mapping posttranscriptional regulation of the human glycome uncovers microRNA defining the glycocode

Abstract

Cell surface glycans form a critical interface with the biological milieu, informing diverse processes from the inflammatory cascade to cellular migration. Assembly of discrete carbohydrate structures requires the coordinated activity of a repertoire of proteins, including glycosyltransferases and glycosidases. Little is known about the regulatory networks controlling this complex biosynthetic process. Recent work points to a role for microRNA (miRNA) in the regulation of specific glycan biosynthetic enzymes. Herein we take a unique systems-based approach to identify connections between miRNA and the glycome. By using our glycomic analysis platform, lectin microarrays, we identify glycosylation signatures in the NCI-60 cell panel that point to the glycome as a direct output of genomic information flow. Integrating our glycomic dataset with miRNA data, we map miRNA regulators onto genes in glycan biosynthetic pathways (glycogenes) that generate the observed glycan structures. We validate three of these predicted miRNA/glycogene regulatory networks: high mannose, fucose, and terminal β-GalNAc, identifying miRNA regulation that would not have been observed by traditional bioinformatic methods. Overall, our work reveals critical nodes in the global glycosylation network accessible to miRNA regulation, providing a bridge between miRNA-mediated control of cell phenotype and the glycome.

Keywords: NCI-60; carbohydrate biosynthesis; epigenetics; glycan regulation; systems biology.

Fig. 1.

Ratiometric comparison of NCI-60 cell lines. (A) Experimental scheme. Equal amounts of Cy5-sample (S) and Cy3-reference (R) were analyzed on the lectin microarray. (B) Median-normalized log₂ ratios (S/R) for 55 cell lines of the NCI-60 were hierarchically clustered by using centered PearCC as the distance metric and average linkage analysis (n = 76 lectins). Heat map is shown. Yellow, log₂(S/R) > log₂(S_median/R_median); blue, log₂(S_median/R_median) > log₂(S/R). (C) Dendrogram from B. As expected, biological replicates for KM12 clustered tightly. PearCC scale is shown at right.

Fig. 2.

Mapping of miRNA/glycosylation networks. (A) SVD of lectin and miRNA data for renal, colon, leukemia (leuk), and melanoma cell lines. The first six eigengenes (E1–E6) are indicated. (B) Hierarchical clustering of the projection correlation values for E1–E6 using uncentered PearCC as the distance metric and average linkage analysis. Select clusters are annotated by glycan specificity. (C) A detailed representation of the high mannose cluster (R = 0.71; one-tailed P = 0.06; n = 6). Lectins are shown in red. (D–F) Networks derived from lectin/miRNA clusters: (D) high mannose network, (E) fucose network, (F) β-GalNAc network. Gray boxes indicate epitopes recognized by lectins. Bubbles indicate predicted miRNA targets, with bubble size reflecting number of miRNA targeting gene. Lines connect miRNA with targets; genes in silver are genes in the pathway that are not targeted.

Fig. 3.

Validation of the high mannose network. (A and B) Representative fluorescence images of HT-29 cells stained with high mannose lectins (A) HHL or (B) PSA following 96 h treatment with miR-30c, -181b-5p, -361–5p, or scramble mimics. Monosaccharide control for staining is shown. Data are representative of three biological replicates. Statistical analysis of the staining and additional lectin data for GNA, NPA, and the LcH control is shown in SI Appendix, Fig. S5. (C–F) Real-time qPCR analysis of indicated glycogenes in HT-29 cells treated with indicated miRNA mimics (50 nM; C and E) or corresponding inhibitors (anti-, 25 nM; D and F) for 72 h. Scrambled sequences are used as a control (scramble). Graphs show average relative expression normalized to GAPDH of three biological replicates. (C and D) MAN1A1. (E and F) MAN1A2. (G and H) Western blot analysis of MAN1A2 samples treated as described with (G) miRNA mimics or (H) inhibitors. Graphs are of average signal normalized to GAPDH for three biological replicates. Representative images corresponding to the graphs are shown. (I) Graphical representation of luciferase activity from MAN1A2 constructs cotransfected with miR-30c, -181b-5p, -361–5p, or scramble mimics (60 nM) in HEK-293T/17 cells. Mut, miR-30 mutant or miR-361–5p mutant construct as indicated (SI Appendix, Fig. S8A and Table S3). Luciferase data were normalized to scramble control. Error bars denote SD (*P < 0.05, Student t test).

Fig. 4.

Validation of the fucose network. (A) Fucose lectin data from Fig. 1B (AAL, UEA-I) arranged to reflect phenotype as previously described (30). Cell lines with high expression of miR-200f are boxed in red (30). (B) Graphical representation of luciferase activity from FUCA2 constructs cotransfected with miR-200b, -200c, -429, or scramble mimics. Mut, FUCA2 mutant as indicated in C. Data were generated as in Fig. 3I. (C) Sequence alignment of miR-200c and FUCA2-3′UTR; mutated bases are shown in red.

Fig. 5.

MiR-200f members down-regulate FUCA2 expression and increase fucosylation in HT-29. (A) Real-time qPCR analysis of FUCA2 mRNA expression in cells treated with miR-200b-3p (200b), -200c-3p (200c), -429, or scramble mimic. Data were generated as in Fig. 3 C and E. (B) Representative fluorescence images of cells treated as in Fig. 3 A and B with indicated miR-200f mimics or scramble and stained with AAL. Monosaccharide inhibition control is shown (Ctrl). Data are representative of three biological replicates; SI Appendix, Fig. S9B provides statistical quantification of staining.

Fig. 6.

Validation of β-GalNAc network. Graphical representation of luciferase activity from ST6GALNAC3 constructs cotransfected with miR-200a-5p, -200b-5p, -205, or scramble mimics. Mut, ST6GALNAC3 mutant (SI Appendix, Table S3). Data were generated as in Fig. 3I.