Dataset Information

Modulating Heparanase Activity: Tuning Sulfation Pattern and Glycosidic Linkage of Oligosaccharides.

ABSTRACT: Heparanase cleaves polymeric heparan sulfate (HS) molecules into smaller oligosaccharides, allowing for release of angiogenic growth factors promoting tumor development and autoreactive immune cells to reach the insulin-producing ? cells. Interaction of heparanase with HS chains is regulated by specific substrate sulfation sequences. We have synthesized 11 trisaccharides that are highly tunable in structure and sulfation pattern, allowing us to determine how heparanase recognizes HS substrate and selects a favorable cleavage site. Our study shows that (1) N-SO3- at +1 subsite and 6-O-SO3- at -2 subsite of trisaccharides are critical for heparanase recognition, (2) addition of 2-O-SO3- at the -1 subsite and of 3-O-SO3- to GlcN unit is not advantageous, and (3) the anomeric configuration (? or ?) at the reducing end is crucial in controlling heparanase activity. Our study also illustrates that the ?-trisaccharide having N- and 6-O-SO3- at -2 and +1 subsites inhibited heparanase and was resistant toward hydrolysis.

SUBMITTER: Zhu S

PROVIDER: S-EPMC7376576 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Modulating Heparanase Activity: Tuning Sulfation Pattern and Glycosidic Linkage of Oligosaccharides.

Zhu Sanyong S Li Jiayi J Loka Ravi S RS Song Zhenfeng Z Vlodavsky Israel I Zhang Kezhong K Nguyen Hien M HM

Journal of medicinal chemistry 20200407 8

Heparanase cleaves polymeric heparan sulfate (HS) molecules into smaller oligosaccharides, allowing for release of angiogenic growth factors promoting tumor development and autoreactive immune cells to reach the insulin-producing β cells. Interaction of heparanase with HS chains is regulated by specific substrate sulfation sequences. We have synthesized 11 trisaccharides that are highly tunable in structure and sulfation pattern, allowing us to determine how heparanase recognizes HS substrate an ...[more]

PMID: 32216347

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Project description:Members of the genus Bifidobacterium are common inhabitants of the gastrointestinal tract of humans and other mammals, where they ferment many diet-derived carbohydrates that cannot be digested by their host. To extend our understanding of bifidobacterial carbohydrate utilisation, we investigated the molecular mechanisms by which various strains of Bifidobacterium breve metabolize four distinct α-glucose and/or α-galactose-containing oligosaccharides, namely raffinose, stachyose, melibiose and melezitose. Here we demonstrate that all B. breve strains examined possess the ability to utilise raffinose, stachyose and melibiose. However, the ability to metabolize melezitose was not ubiquitous for all tested B. breve strains. Transcriptomic and functional genomic approaches identified a gene cluster dedicated to the metabolism of α-galactose-containing carbohydrates, while an adjacent gene cluster, dedicated to the metabolism of α-glucose-containing melezitose, was identified, yet being present only in those B. breve strains that were able to support growth on this carbohydrate. DNA-microarrays containing oligonucleotide primers representing each of the 1864 annotated genes on the genome of B. breve UCC2003 (O'Connell Motherway et al., 2011) were designed by and obtained from Agilent Technologies (Palo Alto, Ca., USA). Methods for cell disruption, RNA isolation, RNA quality control, complementary DNA synthesis and labeling were performed as described previously (Pokusaeva et al., 2009). Labeled cDNA was hybridized using the Agilent Gene Expression hybridization kit (part number 5188-5242) as described in the Agilent Two-Color Microarray-Based Gene Expression Analysis v4.0 manual (G4140-90050). Following hybridization, microarrays were washed in accordance with Agilent’s standard procedures and scanned using an Agilent DNA microarray scanner (model G2565A). Generated scans were converted to data files with Agilent's Feature Extraction software (Version 9.5). DNA-microarray data were processed as previously described (Garcia De La Nava et al., 2003). Differential expression tests were performed with the Cyber-T implementation of a variant of the t-test (Long et al., 2001). A gene was considered differentially expressed when p < 0.001 and an expression ratio of >3 or <0.33 relative to the control.

Dataset Information

Modulating Heparanase Activity: Tuning Sulfation Pattern and Glycosidic Linkage of Oligosaccharides.

Publications

Modulating Heparanase Activity: Tuning Sulfation Pattern and Glycosidic Linkage of Oligosaccharides.

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