Imperial College London

Emeritus ProfessorJeremyNicholson

Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Emeritus Professor of Biological Chemistry
 
 
 
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Contact

 

+44 (0)20 7594 3195j.nicholson Website

 
 
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Assistant

 

Ms Wendy Torto +44 (0)20 7594 3225

 
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Location

 

Office no. 665Sir Alexander Fleming BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@unpublished{Neves:2019:10.1101/602458,
author = {Neves, AL and Rodriguez-Martinez, A and Ayala, R and Posma, JM and Abellona, U MR and Chilloux, J and Nicholson, JK and Dumas, M-E and Hoyles, L},
doi = {10.1101/602458},
publisher = {Cold Spring Harbor Laboratory},
title = {A network-based data-mining approach to investigate indole-related microbiota-host co-metabolism},
url = {http://dx.doi.org/10.1101/602458},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - UNPB
AB - <jats:title>Abstract</jats:title><jats:sec><jats:title>Motivation</jats:title><jats:p>Indoles have been shown to play a significant role in cardiometabolic disorders. While some individual bacterial species are known to produce indole-adducts, to our best knowledge no studies have made use of publicly available genome data to identify prokaryotes, specifically those associated with the human gut microbiota, contributing to the indole metabolic network.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>Here, we propose a computational strategy, comprising the integration of KEGG and BLAST, to identify prokaryote-specific metabolic reactions relevant for the production of indoles, as well as to predict new members of the human gut microbiota potentially involved in these reactions. By identifying relevant prokaryotic species for further validation studies <jats:italic>in vitro</jats:italic>, this strategy represents a useful approach for those interrogating the metabolism of other gut-derived microbial metabolites relevant to human health.</jats:p></jats:sec><jats:sec><jats:title>Availability</jats:title><jats:p>All R scripts and files (gut microbial dataset, FASTA protein sequences, BLASTP output files) are available from <jats:ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://github.com/AndreaRMICL/Microbial_networks">https://github.com/AndreaRMICL/Microbial_networks</jats:ext-link>.</jats:p></jats:sec><jats:sec><jats:title>Contact</jats:title><jats:p>ARM: <jats:email>andrea.rodriguez-martinez13@imperial.ac.uk</jats:email>; LH: <jats:email>lesley.hoyles@ntu.ac.uk</jats:email>.</jats:p></jats:sec>
AU - Neves,AL
AU - Rodriguez-Martinez,A
AU - Ayala,R
AU - Posma,JM
AU - Abellona,U MR
AU - Chilloux,J
AU - Nicholson,JK
AU - Dumas,M-E
AU - Hoyles,L
DO - 10.1101/602458
PB - Cold Spring Harbor Laboratory
PY - 2019///
TI - A network-based data-mining approach to investigate indole-related microbiota-host co-metabolism
UR - http://dx.doi.org/10.1101/602458
ER -