Combining functional metagenomics and glycoanalytics to identify enzymes that facilitate structural characterization of sulfated N-glycans

Abstract

Background Sulfate modification of N-glycans is important for several biological functions such as clearance of pituitary hormones or immunoregulation. Yet, the prevalence of this N-glycan modification and its functions remain largely unexplored. Characterization of N-glycans bearing sulfate modifications is hampered in part by a lack of enzymes that enable site-specific detection of N-glycan sulfation. In this study, we used functional metagenomic screening to identify enzymes that act upon sulfated N-acetylglucosamine (GlcNAc). Using multiplexed capillary gel electrophoresis with laser-induced fluorescence detection (xCGE-LIF) -based glycoanalysis we proved their ability to act upon GlcNAc-6-SO4 on N-glycans. Results Our screen identified a sugar-specific sulfatase that specifically removes sulfate from GlcNAc-6-SO4 when it is in a terminal position on an N-glycan. Additionally, in the absence of calcium, this sulfatase binds to the sulfated glycan but does not remove the sulfate group, suggesting it could be used for selective isolation of sulfated N-glycans. Further, we describe isolation of a sulfate-dependent hexosaminidase that removes intact GlcNAc-6-SO4 (but not asulfated GlcNAc) from a terminal position on N-glycans. Finally, the use of these enzymes to detect the presence of sulfated N-glycans by xCGE-LIF is demonstrated. Conclusion The present study demonstrates the feasibility of using functional metagenomic screening combined with glycoanalytics to discover enzymes that act upon chemical modifications of glycans. The discovered enzymes represent new specificities that can help resolve the presence of GlcNAc-6-SO4 in N-glycan structural analyses.

Deep learning explains the biology of branched glycans from single-cell sequencing data

“…We envision a pipeline in which this explainable DL approach is used to analyze data generated by SUGAR-seq or similar technologies, to decode the biology of less well-studied glycoforms (e.g., high-mannose glycans, sulfated glycans, and I-branched glycans) and their importance in disease ( Chuzel et al., 2021 ; Dimitroff, 2019 ; de Leoz et al., 2011 ; Loke et al., 2016 ; Sun et al., 2022 ). For this, future work needs to expand the capabilities of the associated lectin-seq, similar to the already reported Glycan-seq technology ( Oinam et al., 2021 ).…”

Deep Learning Explains the Biology of Branched Glycans from Single-Cell Sequencing Data

“…We envision a pipeline in which this explainable DL approach is used to analyze data generated by SUGAR-seq or similar technologies, to decode the biology of less well-studied glycoforms (e.g., high-mannose glycans, sulfated glycans, I-branched glycans) and their importance in disease (Chuzel et al, 2021; Dimitroff, 2019; de Leoz et al, 2011; Loke et al, 2016; Sun et al, 2022). For this, future work needs to expand the capabilities of the associated lectin-seq, similar to the already reported Glycan-seq technology (Oinam et al, 2021).…”

“…In line with the immunosuppressive role of β1,6-branched glycans, CCL2 secreted by cancer cells contributes to an immunosuppressive tumor microenvironment, and blockade of CCR2 in mice improved the efficacy of immune checkpoint therapy (Matsuo et al, 2021;Tu et al, 2020), suggesting a direct biomedically relevant role of this glycan feature. We envision a pipeline in which this explainable DL approach is used to analyze data generated by SUGAR-seq or similar technologies, to decode the biology of less well-studied glycoforms (e.g., high-mannose glycans, sulfated glycans, I-branched glycans) and their importance in disease (Chuzel et al, 2021;Dimitroff, 2019;de Leoz et al, 2011;Loke et al, 2016;Sun et al, 2022). For this, future work needs to expand the capabilities of the associated lectin-seq, similar to the already reported Glycan-seq technology (Oinam et al, 2021).…”

Mechanistic and Structural Insights into the Specificity and Biological Functions of Bacterial Sulfoglycosidases

“…Similarly, Prevotella Strain RS2 encodes sulfatases, such as MdsA, while it also has a periplasmic 6S-GlcNAcase, SGL, that releases 6S-GlcNAc from sulfomucin O -glycan (Figure b) . Recently, Bacteroides caccae and Phocaeicola dorei have also been found to encode 6S-GlcNAcases that release 6S-GlcNAc from N -glycans . These bacteria are prominent members of human microbiota.…”

“…Glycan sulfation is a major type of enzyme-catalyzed post-glycosylation modification (PGM) . Sulfation has been found in N - and O -glycans as well as in proteoglycans, including glycosaminoglycans (GAGs), decorating N -acetylglucosamine (6S-GlcNAc), N -acetylgalactosamine (6S-GalNAc and 4S-GalNAc), galactose (3S-Gal, 4S-Gal, and 6S-Gal), and mannose (6S-Man) − (Figure a). Sulfated N -glycans on neuraminidase and hemagglutinin play a role in the antigenicity and elicitation of innate immunity of influenza virus .…”