High-resolution sweep metagenomics using fast probabilistic inference [version 2; peer review: 2 approved]

Tommi Mäklin; Teemu Kallonen; Sophia David; Christine J. Boinett; Ben Pascoe; Guillaume Méric; David M. Aanensen; Edward J. Feil; Stephen Baker; Julian Parkhill; Samuel K. Sheppard; Jukka Corander; Antti Honkela

doi:10.12688/wellcomeopenres.15639.2

High-resolution sweep metagenomics using fast probabilistic inference [version 2; peer review: 2 approved]

Tommi Mäklin, Teemu Kallonen, Sophia David, Christine J. Boinett, Ben Pascoe, Guillaume Méric, David M. Aanensen, Edward J. Feil, Stephen Baker, Julian Parkhill, Samuel K. Sheppard, Jukka Corander, Antti Honkela

Research output: Contribution to journal › Article › peer-review

2 Citations (SciVal)

Abstract

Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and estimating the relative sequence abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our pipeline facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.

Original language	English
Article number	14
Number of pages	20
Journal	Wellcome Open Research
Volume	5
Early online date	30 Jan 2020
DOIs	https://doi.org/10.12688/wellcomeopenres.15639.2
Publication status	Published - 8 Oct 2021

Bibliographical note

Funding Information:
Flagship programme (Finnish Center for Artificial Intelligence FCAI; to JC and AH). TK, JC, DA and EJF are supported by the JPI-AMR consortium SpARK (MR/R00241X/1). JC was funded by the ERC (grant no. 742158). TK was funded by the Norwegian Research Council JPIAMR (grant no. 144501). SB is a Sir Henry Dale Fellow, jointly funded by the Wellcome Trust and the Royal Society [100087]. Sequencing of the Vietnamese E. coli samples was supported by the Wellcome Trust [098051]. Computational resources were provided by the 'Finnish Grid and Cloud Infrastructure' (persistent identifier urn:nbn:fi:research-infras-2016072533).

Funding Information:
Grant information: This work was supported by the Academy of Finland (grants no. 259440 and 310261; to TM and AH) as well as the

Publisher Copyright:
© 2020. Mäklin T et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords

bacterial strain identification
metagenomics
microbial communities
plate sweeps
probabilistic modeling

ASJC Scopus subject areas

Medicine (miscellaneous)
General Biochemistry,Genetics and Molecular Biology

Access to Document

10.12688/wellcomeopenres.15639.2Licence: CC BY

Cite this

Mäklin, T., Kallonen, T., David, S., Boinett, C. J., Pascoe, B., Méric, G., Aanensen, D. M., Feil, E. J., Baker, S., Parkhill, J., Sheppard, S. K., Corander, J., & Honkela, A. (2021). High-resolution sweep metagenomics using fast probabilistic inference [version 2; peer review: 2 approved]. Wellcome Open Research, 5, Article 14. https://doi.org/10.12688/wellcomeopenres.15639.2

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abstract = "Determining the composition of bacterial communities beyond the level of a genus or species is challenging because of the considerable overlap between genomes representing close relatives. Here, we present the mSWEEP pipeline for identifying and estimating the relative sequence abundances of bacterial lineages from plate sweeps of enrichment cultures. mSWEEP leverages biologically grouped sequence assembly databases, applying probabilistic modelling, and provides controls for false positive results. Using sequencing data from major pathogens, we demonstrate significant improvements in lineage quantification and detection accuracy. Our pipeline facilitates investigating cultures comprising mixtures of bacteria, and opens up a new field of plate sweep metagenomics.",

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author = "Tommi M{\"a}klin and Teemu Kallonen and Sophia David and Boinett, {Christine J.} and Ben Pascoe and Guillaume M{\'e}ric and Aanensen, {David M.} and Feil, {Edward J.} and Stephen Baker and Julian Parkhill and Sheppard, {Samuel K.} and Jukka Corander and Antti Honkela",

note = "Funding Information: Flagship programme (Finnish Center for Artificial Intelligence FCAI; to JC and AH). TK, JC, DA and EJF are supported by the JPI-AMR consortium SpARK (MR/R00241X/1). JC was funded by the ERC (grant no. 742158). TK was funded by the Norwegian Research Council JPIAMR (grant no. 144501). SB is a Sir Henry Dale Fellow, jointly funded by the Wellcome Trust and the Royal Society [100087]. Sequencing of the Vietnamese E. coli samples was supported by the Wellcome Trust [098051]. Computational resources were provided by the 'Finnish Grid and Cloud Infrastructure' (persistent identifier urn:nbn:fi:research-infras-2016072533). Funding Information: Grant information: This work was supported by the Academy of Finland (grants no. 259440 and 310261; to TM and AH) as well as the Publisher Copyright: {\textcopyright} 2020. M{\"a}klin T et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.",

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AU - Kallonen, Teemu

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AU - Boinett, Christine J.

AU - Pascoe, Ben

AU - Méric, Guillaume

AU - Aanensen, David M.

AU - Feil, Edward J.

AU - Baker, Stephen

AU - Parkhill, Julian

AU - Sheppard, Samuel K.

AU - Corander, Jukka

AU - Honkela, Antti

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High-resolution sweep metagenomics using fast probabilistic inference [version 2; peer review: 2 approved]

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

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SpARK - The Rates and Routes of Transmission of Multidrug Resistant Klebsiella Clones into the Clinic from Environmental Sources

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High-resolution sweep metagenomics using fast probabilistic inference [version 2; peer review: 2 approved]

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Projects

SpARK - The Rates and Routes of Transmission of Multidrug Resistant Klebsiella Clones into the Clinic from Environmental Sources

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