title: A network-based approach to identify substrate classes of bacterial glycosyltransferases.
abstract: BACKGROUND
  Bacterial 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.
  
  
  RESULTS
  In 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.
  
  
  CONCLUSIONS
  We 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.
authors.forename: Aminael
authors.initials: A
authors.lastname: Sánchez-Rodríguez
authors.forename: Hanne L P
authors.initials: HL
authors.lastname: Tytgat
authors.forename: Joris
authors.initials: J
authors.lastname: Winderickx
authors.forename: Jos
authors.initials: J
authors.lastname: Vanderleyden
authors.affiliation: Department of Microbial and Molecular Systems, KU Leuven, Centre of Microbial and Plant Genetics, Kasteelpark Arenberg 20, box 2460, Leuven B-3001, Belgium. sarah.lebeer@uantwerpen.be.
authors.forename: Sarah
authors.initials: S
authors.lastname: Lebeer
authors.forename: Kathleen
authors.initials: K
authors.lastname: Marchal
mesh_terms: D000595:Amino Acid Sequence; D001426:Bacterial Proteins / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D016123:Campylobacter jejuni / Q000201:enzymology* / Q000378:metabolism; D053263:Gene Regulatory Networks / Q000235:genetics; D006031:Glycosylation; D016695:Glycosyltransferases / Q000737:chemistry / Q000235:genetics* / Q000378:metabolism; D052201:Lacticaseibacillus rhamnosus / Q000201:enzymology* / Q000378:metabolism; D008390:Markov Chains; D013379:Substrate Specificity
chemical_list: D001426:Bacterial Proteins; D016695:Glycosyltransferases