The glycome

Karlyshev, Andrey V.; Ketley, Julian M.; Wren, Brendan W.

doi:10.1016/j.femsre.2005.01.003

Cited by 41 publications

(27 citation statements)

References 78 publications

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“…In addition to recovering all benchmark GTs (those indicated with experimental validation in Additional file 1: Table S1), most other predictions corresponded to previously made GT related annotations in C. jejuni NCTC 11168 that were based on indirect evidence (e.g. through experimental validation in other closely related species), such as the loci comprising the GT genes responsible for the synthesis of LOS ( CJ1133 – CJ1148 ) [38], the GTs for N- ( CJ1121c– CJ1129c ) [33] and O- glycoprotein biosynthesis ( CJ1311 – CJ1333 ) [34] and the CPS biosynthesis cluster ( CJ1416c – CJ1442c ) [39, 40]. In addition, we made a total of 17 new predictions for yet unannotated genes in C. jejuni NCTC 11168 (Additional file 1: Table S1).…”

Section: Resultssupporting

confidence: 64%

“…For instance, for the isolated GTs known to be involved in PG biosynthesis (PBP1B, PBP2A, PBP1A and MurG), our network-based approach suggests an additional role in the glycosylation of proteins that are either involved in the biosynthesis of the PG (LGG_00254) or in cell division (LGG_01280 or FtsI). Substrate promiscuity of GTs is not uncommon in bacteria as for instance in Gram-negative pathogens, enzymes with relaxed specificity are shared between different processes, such as LPS and glycoprotein biosynthesis [4, 38]. Validating the activity of GTs that were predicted to glycosylate proteins- is cumbersome, as in vitro enzymatic assays do not represent the cellular conditions that are relevant for the assembly of these GTs in multi-enzyme membrane-associated complexes [69].…”

Section: Discussionmentioning

confidence: 99%

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A network-based approach to identify substrate classes of bacterial glycosyltransferases

et al. 2014

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BackgroundBacterial interactions with the environment- and/or host largely depend on the bacterial glycome. The specificities of a bacterial glycome are largely determined by glycosyltransferases (GTs), the enzymes involved in transferring sugar moieties from an activated donor to a specific substrate. Of these GTs their coding regions, but mainly also their substrate specificity are still largely unannotated as most sequence-based annotation flows suffer from the lack of characterized sequence motifs that can aid in the prediction of the substrate specificity.ResultsIn this work, we developed an analysis flow that uses sequence-based strategies to predict novel GTs, but also exploits a network-based approach to infer the putative substrate classes of these predicted GTs. Our analysis flow was benchmarked with the well-documented GT-repertoire of Campylobacter jejuni NCTC 11168 and applied to the probiotic model Lactobacillus rhamnosus GG to expand our insights in the glycosylation potential of this bacterium. In L. rhamnosus GG we could predict 48 GTs of which eight were not previously reported. For at least 20 of these GTs a substrate relation was inferred.ConclusionsWe confirmed through experimental validation our prediction of WelI acting upstream of WelE in the biosynthesis of exopolysaccharides. We further hypothesize to have identified in L. rhamnosus GG the yet undiscovered genes involved in the biosynthesis of glucose-rich glycans and novel GTs involved in the glycosylation of proteins. Interestingly, we also predict GTs with well-known functions in peptidoglycan synthesis to also play a role in protein glycosylation.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-349) contains supplementary material, which is available to authorized users.

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Section: Resultssupporting

confidence: 64%

Section: Discussionmentioning

confidence: 99%

A network-based approach to identify substrate classes of bacterial glycosyltransferases

et al. 2014

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“…However, H. pylori possesses a complete pentose phosphate pathway and an Entner–Doudoroff pathway (Doig et al, 1999) that enable the catabolism of glucose to pyruvate (Mendz et al, 1994), while C. jejuni does not encode for the glucose-6-phosphate dehydrogenase (EC 1.1.1.49) and the 6-phosphogluconolactonase (EC 3.1.1.31) of the oxidative pentose phosphate pathway branch but harbors all enzymes of the reductive branch of the pentose phosphate pathway (Parkhill et al, 2000; Fouts et al, 2005). Consequently, gluconeogenesis seems to be required for the biosynthesis of glucose and its derivatives that are precursor substrates for the LPS and capsule biosynthesis as well as the N- and O-glycosylation of various secreted proteins (Karlyshev et al, 2005). The genome of C. jejuni harbors all enzymes necessary for gluconeogenic synthesis of glucose from phosphoenolpyruvate (PEP) (Parkhill et al, 2000), but gluconeogenesis has not been experimentally proven yet.…”

Section: Finding a Nutritional Niche: The Low-carb High-protein Dietmentioning

confidence: 99%

Defining the metabolic requirements for the growth and colonization capacity of Campylobacter jejuni

Hofreuter

2014

Front. Cell. Infect. Microbiol.

118

114

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During the last decade Campylobacter jejuni has been recognized as the leading cause of bacterial gastroenteritis worldwide. This facultative intracellular pathogen is a member of the Epsilonproteobacteria and requires microaerobic atmosphere and nutrient rich media for efficient proliferation in vitro. Its catabolic capacity is highly restricted in contrast to Salmonella Typhimurium and other enteropathogenic bacteria because several common pathways for carbohydrate utilization are either missing or incomplete. Despite these metabolic limitations, C. jejuni efficiently colonizes various animal hosts as a commensal intestinal inhabitant. Moreover, C. jejuni is tremendously successful in competing with the human intestinal microbiota; an infectious dose of few hundreds bacteria is sufficient to overcome the colonization resistance of humans and can lead to campylobacteriosis. Besides the importance and clear clinical manifestation of this disease, the pathogenesis mechanisms of C. jejuni infections are still poorly understood. In recent years comparative genome sequence, transcriptome and metabolome analyses as well as mutagenesis studies combined with animal infection models have provided a new understanding of how the specific metabolic capacity of C. jejuni drives its persistence in the intestinal habitat of various hosts. Furthermore, new insights into the metabolic requirements that support the intracellular survival of C. jejuni were obtained. Because C. jejuni harbors distinct properties in establishing an infection in comparison to pathogenic Enterobacteriaceae, it represents an excellent organism for elucidating new aspects of the dynamic interaction and metabolic cross talk between a bacterial pathogen, the microbiota and the host.

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“…Due to the apparent loss of sialylation in the lower M r LOS structure it is likely that the variation of the structure is attributable to functional differences in the synthesis of the transport machinery of sialic acid under the different temperatures. We consider the most likely candidate for this difference to be the dual functioning enzyme, GalNAc transferase and CMP-Neu5Ac synthase, CgtA [18]. …”

Section: Discussionmentioning

confidence: 99%

“…To date, a number of genes from the LOS biosynthesis cluster of C. jejuni NCTC 11168 (HS:2) have been characterized [4,18] and the structures of the lipid A and saccharide components of the LOS have been reported [19-21]. The LOS outer core mimics the oligosaccharide (OS) region of GM 1 ganglioside [20,21] and is likely to be capable of switching from a GM 1 -like epitope to a GM 2 -like epitope as a result of phase variation [22,23].…”

Section: Introductionmentioning

confidence: 99%

Temperature-dependent phenotypic variation of Campylobacter jejuni lipooligosaccharides

et al. 2010

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BackgroundCampylobacter jejuni is a major bacterial cause of food-borne enteritis, and its lipooligosaccharide (LOS) plays an initiating role in the development of the autoimmune neuropathy, Guillain-Barré syndrome, by induction of anti-neural cross-reactive antibodies through ganglioside molecular mimicry.ResultsHerein we describe the existence and heterogeneity of multiple LOS forms in C. jejuni strains of human and chicken origin grown at 37°C and 42°C, respectively, as determined on sodium dodecyl sulphate-polyacrylamide electrophoresis gels with carbohydrate-specific silver staining and blotting with anti-ganglioside ligands, and confirmed by nuclear magnetic resonance (NMR) spectroscopy. The C. jejuni NCTC 11168 original isolate (11168-O) was compared to its genome-sequenced variant (11168-GS), and both were found to have a lower-Mr LOS form, which was different in size and structure to the previously characterized higher-Mr form bearing GM1 mimicry. The lower-Mr form production was found to be dependent on the growth temperature as the production of this form increased from ~5%, observed at 37°C to ~35% at 42°C. The structure of the lower-Mr form contained a β-D-Gal-(1→3)-β-D-GalNAc disaccharide moiety which is consistent with the termini of the GM1, asialo-GM1, GD1, GT1 and GQ1 gangliosides, however, it did not display GM1 mimicry as assessed in blotting studies but was shown in NMR to resemble asialo-GM1. The production of multiple LOS forms and lack of GM1 mimicry was not a result of phase variation in the genes tested of NCTC 11168 and was also observed in most of the human and chicken isolates of C. jejuni tested.ConclusionThe presence of differing amounts of LOS forms at 37 and 42°C, and the variety of forms observed in different strains, indicate that LOS form variation may play a role in an adaptive mechanism or a stress response of the bacterium during the colonization of different hosts.

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The glycome

Cited by 41 publications

References 78 publications

A network-based approach to identify substrate classes of bacterial glycosyltransferases

A network-based approach to identify substrate classes of bacterial glycosyltransferases

Defining the metabolic requirements for the growth and colonization capacity of Campylobacter jejuni

Temperature-dependent phenotypic variation of Campylobacter jejuni lipooligosaccharides

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