Imperial College London
Alternate

ProfessorJulianMarchesi

Faculty of Medicine, Department of Metabolism, Digestion and Reproduction

Professor of Digestive Health
 
 
 
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Contact

 

+44 (0)20 3312 6197j.marchesi

 
 
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Location

 

Queen Elizabeth the Queen Mother Wing (QEQM)St Mary's Campus

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Summary

 

Publications

Citation

BibTex format

@article{O'Sullivan:2021:10.1038/s41598-021-89881-2,
author = {O'Sullivan, DM and Doyle, RM and Temisak, S and Redshaw, N and Whale, AS and Logan, G and Huang, J and Fischer, N and Amos, GCA and Preston, MD and Marchesi, JR and Wagner, J and Parkhill, J and Motro, Y and Denise, H and Finn, RD and Harris, KA and Kay, GL and O'Grady, J and Ransom-Jones, E and Wu, H and Laing, E and Studholme, DJ and Benavente, ED and Phelan, J and Clark, TG and Moran-Gilad, J and Huggett, JF},
doi = {10.1038/s41598-021-89881-2},
journal = {Scientific Reports},
title = {An inter-laboratory study to investigate the impact of the bioinformatics component on microbiome analysis using mock communities},
url = {http://dx.doi.org/10.1038/s41598-021-89881-2},
volume = {11},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - Despite the advent of whole genome metagenomics, targeted approaches (such as 16S rRNA gene amplicon sequencing) continue to be valuable for determining the microbial composition of samples. Amplicon microbiome sequencing can be performed on clinical samples from a normally sterile site to determine the aetiology of an infection (usually single pathogen identification) or samples from more complex niches such as human mucosa or environmental samples where multiple microorganisms need to be identified. The methodologies are frequently applied to determine both presence of micro-organisms and their quantity or relative abundance. There are a number of technical steps required to perform microbial community profiling, many of which may have appreciable precision and bias that impacts final results. In order for these methods to be applied with the greatest accuracy, comparative studies across different laboratories are warranted. In this study we explored the impact of the bioinformatic approaches taken in different laboratories on microbiome assessment using 16S rRNA gene amplicon sequencing results. Data were generated from two mock microbial community samples which were amplified using primer sets spanning five different variable regions of 16S rRNA genes. The PCR-sequencing analysis included three technical repeats of the process to determine the repeatability of their methods. Thirteen laboratories participated in the study, and each analysed the same FASTQ files using their choice of pipeline. This study captured the methods used and the resulting sequence annotation and relative abundance output from bioinformatic analyses. Results were compared to digital PCR assessment of the absolute abundance of each target representing each organism in the mock microbial community samples and also to analyses of shotgun metagenome sequence data. This ring trial demonstrates that the choice of bioinformatic analysis pipeline alone can result in different estimations of the c
AU  - O'Sullivan,DM
AU  - Doyle,RM
AU  - Temisak,S
AU  - Redshaw,N
AU  - Whale,AS
AU  - Logan,G
AU  - Huang,J
AU  - Fischer,N
AU  - Amos,GCA
AU  - Preston,MD
AU  - Marchesi,JR
AU  - Wagner,J
AU  - Parkhill,J
AU  - Motro,Y
AU  - Denise,H
AU  - Finn,RD
AU  - Harris,KA
AU  - Kay,GL
AU  - O'Grady,J
AU  - Ransom-Jones,E
AU  - Wu,H
AU  - Laing,E
AU  - Studholme,DJ
AU  - Benavente,ED
AU  - Phelan,J
AU  - Clark,TG
AU  - Moran-Gilad,J
AU  - Huggett,JF
DO  - 10.1038/s41598-021-89881-2
PY  - 2021///
SN  - 2045-2322
TI  - An inter-laboratory study to investigate the impact of the bioinformatics component on microbiome analysis using mock communities
T2  - Scientific Reports
UR  - http://dx.doi.org/10.1038/s41598-021-89881-2
UR  - https://www.ncbi.nlm.nih.gov/pubmed/34012005
UR  - http://hdl.handle.net/10044/1/91390
VL  - 11
ER  -
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