Journal
BIOCHEMICAL SOCIETY TRANSACTIONS
Volume 38, Issue -, Pages 1290-1293Publisher
PORTLAND PRESS LTD
DOI: 10.1042/BST0381290
Keywords
bioinformatics; Campylobacter jejuni; glycan biosynthesis; glycome; Inductive Logic Programming (ILP); systems microbiology
Categories
Funding
- Biotechnology and Biological Sciences Research Council [BB/C519670/1]
- BBSRC [BB/F009321/1] Funding Source: UKRI
- Biotechnology and Biological Sciences Research Council [BB/C519670/1, BB/F009321/1] Funding Source: researchfish
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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.
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