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Systems analysis of bacterial glycomes.
Kay, Emily; Lesk, Victor I; Tamaddoni-Nezhad, Alireza; Hitchen, Paul G; Dell, Anne; Sternberg, Michael J; Muggleton, Stephen; Wren, Brendan W.
Afiliación
  • Kay E; The Centre for Integrative Systems Biology, Imperial College, London SW7 2AZ, UK.
Biochem Soc Trans ; 38(5): 1290-3, 2010 Oct.
Article en En | MEDLINE | ID: mdl-20863301
Bacteria produce an array of glycan-based structures including capsules, lipo-oligosaccharide and glycosylated proteins, which are invariably cell-surface-located. For pathogenic bacteria, such structures are involved in diverse roles in the life cycle of the bacterium, including adhesion, colonization, avoidance of predation and interactions with the immune system. Compared with eukaryotes, bacteria produce huge combinatorial variations of glycan structures, which, coupled to the lack of genetic data, has previously hampered studies on bacterial glycans and their role in survival and pathogenesis. The advent of genomics in tandem with rapid technological improvements in MS analysis has opened a new era in bacterial glycomics. This has resulted in a rich source of novel glycan structures and new possibilities for glycoprospecting and glycoengineering. However, assigning genetic information in predicted glycan biosynthetic pathways to the overall structural information is complex. Bioinformatic analysis is required, linked to systematic mutagenesis and functional analysis of individual genes, often from diverse biosynthetic pathways. This must then be related back to structural analysis from MS or NMR spectroscopy. To aid in this process, systems level analysis of the multiple datasets can be used to make predictions of gene function that can then be confirmed experimentally. The present paper exemplifies these advances with reference to the major gastrointestinal pathogen Campylobacter jejuni.
Asunto(s)

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Bacterias / Biología Computacional / Glicómica Idioma: En Revista: Biochem Soc Trans Año: 2010 Tipo del documento: Article

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Bacterias / Biología Computacional / Glicómica Idioma: En Revista: Biochem Soc Trans Año: 2010 Tipo del documento: Article