GlycobiologyMicrobiologyPeer-reviewed journal article
Glycoengineering with neuraminic acid analogs to label lipooligosaccharides and detect native sialyltransferase activity in Gram-negative bacteria
Erianna I. Alvarado-MelendeziD, Hanna de JongiD, Jet E. M. Hartman, Jun Yang OngiD, Marc M. S. M. WösteniD, Tom WennekesiD
Abstract
Lipooligosaccharides (LOS) are the most abundant cell surface glycoconjugates on the outer membrane of Gram-negative bacteria. They play important roles in host-microbe interactions. Certain Gram-negative pathogenic bacteria cap their LOS with the sialic acid, N-acetylneuraminic acid (Neu5Ac), to mimic host glycans that among others protects these bacteria from recognition by the hosts immune system. This process of molecular mimicry is not fully understood and remains under investigated. To explore the functional role of sialic acid-capped lipooligosaccharides (LOS) at the molecular level, it is important to have tools readily available for the detection and manipulation of both Neu5Ac on glycoconjugates and the involved sialyltransferases, preferably in live bacteria. We and others have shown that the native sialyltransferases of some Gram-negative bacteria can incorporate extracellular unnatural sialic acid nucleotides onto their LOS. We here report on the expanded use of native bacterial sialyltransferases to incorporate neuraminic acids analogs with a reporter group into the LOS of a variety of Gram-negative bacteria. We show that this approach offers a quick strategy to screen bacteria for the expression of functional sialyltransferases and the ability to use exogenous CMP-Neu5Ac to decorate their glycoconjugates. For selected bacteria we also show this strategy complements two other glycoengineering techniques, Metabolic Oligosaccharide Engineering (MOE) and Selective Exo-Enzymatic Labelling (SEEL), and that together they provide tools to modify, label, detect and visualize sialylation of bacterial LOS.
- organism: bacteria (other)
- assay: proteomics
- research focus: host-pathogen & immune response
- approach: experimental assay
- Citations
- 6
- FWCI
- 0.69
- Field percentile
- top 37%
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