High-throughput analysis of B3GLCT regulation predicts phenotype of Peters’ Plus Syndrome in line with the miRNA Proxy Hypothesis

Abstract

MicroRNAs (miRNAs, miRs) finely tune protein expression and target networks of 100s-1000s of genes that control specific biological processes. They are critical regulators of glycosylation, one of the most diverse and abundant posttranslational modifications. In recent work, miRs have been shown to predict the biological functions of glycosylation enzymes, leading to the miRNA proxy hypothesis which states, if a miR drives a specific biological phenotype, the targets of that miR will drive the same biological phenotype. Testing of this powerful hypothesis is hampered by our lack of knowledge about miR targets. Target prediction suffers from low accuracy and a high false prediction rate. Herein, we develop a high-throughput experimental platform to analyze miR:target interactions, miRFluR. We utilize this system to analyze the interactions of the entire human miRome with beta-3-glucosyltransferase (B3GLCT), a glycosylation enzyme whose loss underpins the congenital disorder Peters Plus Syndrome. Although this enzyme is predicted by multiple algorithms to be highly targeted by miRs, we identify only 27 miRs that downregulate B3GLCT, a >96% false positive rate for prediction. Functional enrichment analysis of these validated miRs predict phenotypes associated with Peters Plus Syndrome, although B3GLCT is not in their known target network. Thus, biological phenotypes driven by B3GLCT may be driven by the target networks of miRs that regulate this enzyme, providing additional evidence for the miRNA Proxy Hypothesis.

High-Throughput Analysis Reveals miRNA Upregulating α-2,6-Sialic Acid through Direct miRNA–mRNA Interactions

“…We recently established a high-throughput fluorescence assay, miRFluR, that enables interrogation of the entire cohort of human miRNA against the 3′-UTR of a single gene. 28 Our comprehensive analysis showed intriguing hints that upregulation of protein expression might not be limited to nondividing cells. Herein we apply our assay to analyze the regulation of ST6GAL1 and ST6GAL2, the enzymes underlying α-2,6-sialic acid.…”

“…55 Our previous miRFluR analysis of miRNAmediated regulation for B3GLCT also identified potential up-miRs for that enzyme. 28 These interactions have been missed by the scientific community because the current pathway for identifying miRNA interactions has depended on validating potential targets of miRNAs predicted by Targetscan and other algorithms that are focused on downregulation. Recent work knocking out AGO complexes found that removal of the miRNA machinery caused most genes to lose expression, consistent with upregulation being a primary function of miRNA, rather than the expected gain that would come from loss of a repressor.…”

“…As upregulation was a surprising finding, we validated twice the number of up-miRs and prioritized miRNA with known roles in the literature. 31−34 To ensure that our findings were reproducible across cell types, we tested four cancer cell lines: A549 (lung, Figure 3 28 Overall, up-and down-miRs had the anticipated impact on ST6GAL1 protein levels. Although we observed a few cell-specific differences, most notably for downmiRs (miR-499a-5p, miR-216a-3p), in all cases the expected result was observed in at least one cell line, validating the accuracy of our assay.…”

“…To understand the role miRNA might play in ST6GAL1 regulation, we used our miRFluR assay. 28 This assay uses a genetically encoded ratiometric sensor containing the fluorescent protein Cerulean under the control of the 3′-UTR of the protein of interest and a control fluorophore mCherry (Figure 2a). miRNA downregulating protein expression (down-miRs) would cause a loss of Cerulean signal, and conversely miRNA upregulating protein expression (up-miRs) would cause a gain of Cerulean signal.…”

“…This follows data from multiple studies showing discrepancies between mRNA transcript and protein levels. 16,28,35,36 We also tested the impact of up-and down-miRs targeting ST6GAL1 on α-2,6-sialylation using the α-2,6-sialic acid specific Sambucus nigra lectin (SNA). 37 Our results were consistent with the effects of miRNA on protein expression, with up-miRs increasing and down-miRs decreasing α-2,6-sialic acid levels in both A549 cells (Figure 3c, Supporting Information Figure S4) and PANC1 (Supporting Information Figure S5e−f).…”