Data_Sheet_3_Cell Line-, Protein-, and Sialoglycosite-Specific Control of Flux-Based Sialylation in Human Breast Cells: Implications for Cancer Progre.xlsx (558.48 kB)

Data_Sheet_3_Cell Line-, Protein-, and Sialoglycosite-Specific Control of Flux-Based Sialylation in Human Breast Cells: Implications for Cancer Progression.xlsx

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posted on 05.02.2020 by Christopher T. Saeui, Kyung-cho Cho, Vrinda Dharmarha, Alison V. Nairn, Melina Galizzi, Sagar R. Shah, Prateek Gowda, Marian Park, Melissa Austin, Amelia Clarke, Edward Cai, Matthew J. Buettner, Ryan Ariss, Kelley W. Moremen, Hui Zhang, Kevin J. Yarema

Sialylation, a post-translational modification that impacts the structure, activity, and longevity of glycoproteins has been thought to be controlled primarily by the expression of sialyltransferases (STs). In this report we explore the complementary impact of metabolic flux on sialylation using a glycoengineering approach. Specifically, we treated three human breast cell lines (MCF10A, T-47D, and MDA-MB-231) with 1,3,4-O-Bu3ManNAc, a “high flux” metabolic precursor for the sialic acid biosynthetic pathway. We then analyzed N-glycan sialylation using solid phase extraction of glycopeptides (SPEG) mass spectrometry-based proteomics under conditions that selectively captured sialic acid-containing glycopeptides, referred to as “sialoglycosites.” Gene ontology (GO) analysis showed that flux-based changes to sialylation were broadly distributed across classes of proteins in 1,3,4-O-Bu3ManNAc-treated cells. Only three categories of proteins, however, were “highly responsive” to flux (defined as two or more sialylation changes of 10-fold or greater). Two of these categories were cell signaling and cell adhesion, which reflect well-known roles of sialic acid in oncogenesis. A third category—protein folding chaperones—was unexpected because little precedent exists for the role of glycosylation in the activity of these proteins. The highly flux-responsive proteins were all linked to cancer but sometimes as tumor suppressors, other times as proto-oncogenes, or sometimes both depending on sialylation status. A notable aspect of our analysis of metabolically glycoengineered breast cells was decreased sialylation of a subset of glycosites, which was unexpected because of the increased intracellular levels of sialometabolite “building blocks” in the 1,3,4-O-Bu3ManNAc-treated cells. Sites of decreased sialylation were minor in the MCF10A (<25% of all glycosites) and T-47D (<15%) cells but dominated in the MDA-MB-231 line (~60%) suggesting that excess sialic acid could be detrimental in advanced cancer and cancer cells can evolve mechanisms to guard against hypersialylation. In summary, flux-driven changes to sialylation offer an intriguing and novel mechanism to switch between context-dependent pro- or anti-cancer activities of the several oncoproteins identified in this study. These findings illustrate how metabolic glycoengineering can uncover novel roles of sialic acid in oncogenesis.

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