2022
DOI: 10.1093/glycob/cwac069
|View full text |Cite
|
Sign up to set email alerts
|

Elucidation of the O-antigen structure of Escherichia coli O93 and characterization of its biosynthetic genes

Abstract: The structure of the O-antigen from the international reference strain Escherichia coli O93:−:H16 has been determined. A nonrandom modal chain-length distribution was observed for the lipopolysaccharide, a pattern which is typical when long O-specific polysaccharides are expressed. By a combination of (i) bioinformatics information on the gene cluster related to O-antigen synthesis including putative function on glycosyl transferases, (ii) the magnitude of NMR coupling constants of anomeric protons and (iii) u… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2024
2024
2024
2024

Publication Types

Select...
2

Relationship

1
1

Authors

Journals

citations
Cited by 2 publications
(1 citation statement)
references
References 67 publications
0
1
0
Order By: Relevance
“…The ability to predict NMR chemical shifts of molecules by machine learning, understand the biology of branched N -glycans, or unveil the origin of glycan-mediated host-microbe interactions by deep learning methods opens new avenues for exploring the importance of glycan structure in biology using NMR spectroscopy as the experimental technique. With the introduction of AlphaFold to predict three-dimensional structure of proteins, analysis of carbohydrate binding proteins, structures of glycosyl transferases, and possible functions of proteins as well as modules thereof has been completely changed. One can now with confidence first investigate whether a sequence of amino acids of a protein or a subset of these have a defined three-dimensional structure, and if this is the case, a construct can be made to check the prediction by NMR spectroscopy (Figure ), prior to trying to elucidate the function of the module or of the whole protein.…”
Section: Outlook and Summarymentioning
confidence: 99%
“…The ability to predict NMR chemical shifts of molecules by machine learning, understand the biology of branched N -glycans, or unveil the origin of glycan-mediated host-microbe interactions by deep learning methods opens new avenues for exploring the importance of glycan structure in biology using NMR spectroscopy as the experimental technique. With the introduction of AlphaFold to predict three-dimensional structure of proteins, analysis of carbohydrate binding proteins, structures of glycosyl transferases, and possible functions of proteins as well as modules thereof has been completely changed. One can now with confidence first investigate whether a sequence of amino acids of a protein or a subset of these have a defined three-dimensional structure, and if this is the case, a construct can be made to check the prediction by NMR spectroscopy (Figure ), prior to trying to elucidate the function of the module or of the whole protein.…”
Section: Outlook and Summarymentioning
confidence: 99%