Cell-Selective Metabolic Glycan Labeling Based on Ligand-Targeted Liposomes

A cell-specific metabolic glycan labeling strategy has been developed using azidosugars encapsulated in ligand-targeted liposomes. The ligands are designed to bind specific cell-surface receptors that are only expressed or up-regulated in target cells, which mediates the intracellular delivery of azidosugars. The delivered azidosugars are metabolically incorporated into cell-surface glycans, which are then imaged via a bioorthogonal reaction

Gene networks of differentially expressed genes involved in significant pathways.

<p>The gene networks comprised of the differentially expressed genes involved in significant pathways of (A) A/J mice infected with SS2 and (B) B6 mice infected with SS2 are shown. Legend: each circle represents a gene; red, upregulation; blue, downregulation; line segment, interaction of genes; arrow, activation (a), flat-ended arrow, inhibition (inh); straight, binding (b); dashed line, indirect effect (ind); P, phosphorylation; dp, dephosphorylation; ex, expression; u, ubiquitination.</p

Confirmation of BeadChips results by qRT-PCR.

<p>Confirmation of BeadChips results by qRT-PCR.</p

The process of treatment of four groups of data for GO, pathway and gene network analysis.

<p>(a) The differentially expressed genes between control A/J and control B6 mice were eliminated from those between SS2-infected A/J and SS2-infected B6 mice. (b) The remain of differential genes between SS2-infected A/J and SS2-infected B6 were intersected with differentially expressed genes between SS2-infected A/J and control A/J mice. (c) The remaining set of differentially expressed genes were analyzed for inclusion in GO categories and pathways. The same process was carried out with the differentially expressed genes between SS2-infected B6 and control B6 mice.</p

KEGG pathway analysis for significantly differentially expressed genes (A) between SS2-infected A/J and control A/J mice and (B) between SS2-infected B6 and control B6 mice.

<p><i>P</i> value<0.05 and FDR<0.05 were used as thresholds to select significant KEGG pathways. LgP is the base 10 logarithm of the <i>P</i> value.</p

Comparative analysis of gene expression in peritoneal macrophages.

<p>Expression levels of <i>Tlr2</i>, <i>Tnf</i>, <i>Ptx3</i> and <i>Mmp9</i> in A/J and B6 mice were measured by qRT-PCR and normalized to the housekeeping gene <i>GAPDH</i>. Differences between A/J and B6 mice were statistically significant with a <i>P</i> value of <0.05 as determined by one-way ANOVA, except with the <i>Tlr2</i> gene.</p

GO categories of biological processes for significantly differentially expressed genes.

<p>(A) between SS2-infected A/J and control A/J mice and (B) between SS2-infected B6 and control B6 mice. <i>P</i> value<0.05 and FDR<0.05 were used as thresholds to select significant GO categories.</p

LD50 of strain HA9801 on A/J mouse.

<p>LD50 of strain HA9801 on A/J mouse.</p

Primers for selected genes analyzed using qRT-PCR.

<p>Primers for selected genes analyzed using qRT-PCR.</p

Glycan Imaging in Intact Rat Hearts and Glycoproteomic Analysis Reveal the Upregulation of Sialylation during Cardiac Hypertrophy

In the heart, glycosylation is involved in a variety of physiological and pathological processes. Cardiac glycosylation is dynamically regulated, which remains challenging to monitor <i>in vivo</i>. Here we describe a chemical approach for analyzing the dynamic cardiac glycome by metabolically labeling the cardiac glycans with azidosugars in living rats. The azides, serving as a chemical reporter, are chemoselectively conjugated with fluorophores using copper-free click chemistry for glycan imaging; derivatizing azides with affinity tags allows enrichment and proteomic identification of glycosylated cardiac proteins. We demonstrated this methodology by visualization of the cardiac sialylated glycans in intact hearts and identification of more than 200 cardiac proteins modified with sialic acids. We further applied this methodology to investigate the sialylation in hypertrophic hearts. The imaging results revealed an increase of sialic acid biosynthesis upon the induction of cardiac hypertrophy. Quantitative proteomic analysis identified multiple sialylated proteins including neural cell adhesion molecule 1, T-kininogens, and α₂-macroglobulin that were upregulated during hypertrophy. The methodology may be further extended to other types of glycosylation, as exemplified by the mucin-type O-linked glycosylation. Our results highlight the applications of metabolic glycan labeling coupled with bioorthogonal chemistry in probing the biosynthesis and function of cardiac glycome during pathophysiological responses