Imperial College London
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Professor David MacIntyre

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Professor in Reproduction Systems Medicine
 
 
 
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Contact

 

+44 (0)20 7594 2195d.macintyre Website

 
 
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Location

 

Institute of Reproductive and Developmental BiologyHammersmith Campus

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Summary

 

Publications

Citation

BibTex format

@unpublished{Bonnardel:2020:10.1101/2020.09.10.291781,
author = {Bonnardel, F and Haslam, SM and Dell, A and Feizi, T and Liu, Y and Tajadura-Ortega, V and Akune, Y and Sykes, L and Bennett, PR and MacIntyre, DA and Lisacek, F and Imberty, A},
doi = {10.1101/2020.09.10.291781},
publisher = {Nature Research},
title = {Proteome-wide prediction of bacterial carbohydrate-binding proteins as a tool for understanding commensal and pathogen colonisation of the vaginal microbiome},
url = {http://dx.doi.org/10.1101/2020.09.10.291781},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - UNPB
AB  - <jats:title>Abstract</jats:title><jats:p>Bacteria use protein receptors called lectins to anchor to specific host surface sugars. The role of lectins in the vaginal microbiome, and their involvement in reproductive tract pathophysiology is poorly defined. Here we establish a classification system based on taxonomy and protein 3D structure to identify 109 lectin classes. Hidden Markov Model (HMM) profiles for each class were used to search bacterial genomes, resulting in the prediction of >100 000 bacterial lectins available at unilectin.eu/bacteria. Genome screening of 90 isolates from 21 vaginal bacterial species showed that potential pathogens produce a larger variety of lectins than commensals indicating increased glycan-binding potential. Both the number of predicted bacterial lectins, and their specificities for carbohydrates correlated with pathogenicity. This study provides new insights into potential mechanisms of commensal and pathogen colonisation of the reproductive tract that underpin health and disease states.</jats:p>
AU  - Bonnardel,F
AU  - Haslam,SM
AU  - Dell,A
AU  - Feizi,T
AU  - Liu,Y
AU  - Tajadura-Ortega,V
AU  - Akune,Y
AU  - Sykes,L
AU  - Bennett,PR
AU  - MacIntyre,DA
AU  - Lisacek,F
AU  - Imberty,A
DO  - 10.1101/2020.09.10.291781
PB  - Nature Research
PY  - 2020///
TI  - Proteome-wide prediction of bacterial carbohydrate-binding proteins as a tool for understanding commensal and pathogen colonisation of the vaginal microbiome
UR  - http://dx.doi.org/10.1101/2020.09.10.291781
ER  -
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