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  3. Exploring the sequence-function space of microbial fucosidases

Exploring the sequence-function space of microbial fucosidases

  • Commun Chem. 2024 Jun 18;7(1):137. doi: 10.1038/s42004-024-01212-4.
Ana Martínez Gascueña # 1,  Haiyang Wu # 1 2,  Rui Wang # 3 4 5,  C David Owen 6 7,  Pedro J Hernando 1 8,  Serena Monaco 9,  Matthew Penner 6 7,  Ke Xing 5,  Gwenaelle Le Gall 10,  Richard Gardner 11,  Didier Ndeh 1 12,  Paulina A Urbanowicz 11,  Daniel I R Spencer 11,  Martin Walsh 6 7,  Jesus Angulo 9 13 14,  Nathalie Juge 15
Affiliations

Affiliations

  • 1 The Gut Microbes and Health Institute Strategic Programme, Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK.
  • 2 GuangDong Engineering Technology Research Center of Enzyme and Biocatalysis, Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou, China.
  • 3 Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing, China.
  • 4 Collaborative Innovation Center of Railway Traffic Safety, Beijing Jiaotong University, Beijing, China.
  • 5 School of Computer and Information Technology, Beijing Jiaotong University, Beijing, China.
  • 6 Diamond Light Source Ltd, Diamond House, Harwell Science and Innovation Campus, Didcot, OX11 0FA, UK.
  • 7 Research Complex at Harwell, Rutherford Appleton Laboratory, Harwell Oxford, Didcot, OX11 0FA, UK.
  • 8 Iceni Glycoscience Ltd., Norwich Research Park, Norwich, NR4 7JG, UK.
  • 9 School of Pharmacy, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
  • 10 Norwich Medical School, University of East Anglia, Norwich Research Park, Norwich, NR4 7TJ, UK.
  • 11 Ludger Ltd, Culham Science Centre, Abingdon, OX14 3EB, UK.
  • 12 University of Dundee, School of Life Sciences, Dundee, DD1 5EH, Scotland, UK.
  • 13 Departamento de Química Orgánica, Universidad de Sevilla, 41012, Sevilla, Spain.
  • 14 Instituto de Investigaciones Químicas (CSIC-US), 41092, Sevilla, Spain.
  • 15 The Gut Microbes and Health Institute Strategic Programme, Quadram Institute Bioscience, Norwich Research Park, Norwich, NR4 7UQ, UK. nathalie.juge@quadram.ac.uk.
  • # Contributed equally.
PMID: 38890439 DOI: 10.1038/s42004-024-01212-4
Abstract

Microbial α-L-fucosidases catalyse the hydrolysis of terminal α-L-fucosidic linkages and can perform transglycosylation reactions. Based on sequence identity, α-L-fucosidases are classified in glycoside hydrolases (GHs) families of the carbohydrate-active enzyme database. Here we explored the sequence-function space of GH29 fucosidases. Based on sequence similarity network (SSN) analyses, 15 GH29 α-L-fucosidases were selected for functional characterisation. HPAEC-PAD and LC-FD-MS/MS analyses revealed substrate and linkage specificities for α1,2, α1,3, α1,4 and α1,6 linked fucosylated oligosaccharides and glycoconjugates, consistent with their SSN clustering. The structural basis for the substrate specificity of GH29 fucosidase from Bifidobacterium asteroides towards α1,6 linkages and FA2G2 N-glycan was determined by X-ray crystallography and STD NMR. The capacity of GH29 fucosidases to carry out transfucosylation reactions with GlcNAc and 3FN as acceptors was evaluated by TLC combined with ESI-MS and NMR. These experimental data supported the use of SSN to further explore the GH29 sequence-function space through machine-learning models. Our lightweight protein language models could accurately allocate test sequences in their respective SSN clusters and assign 34,258 non-redundant GH29 sequences into SSN clusters. It is expected that the combination of these computational approaches will be used in the future for the identification of novel GHs with desired specificities.

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