Bacterial Genomic Epidemiology with Mixed Samples

Tommi Mäklin; Teemu Kallonen; Jarno Alanko; Ørjan Samuelsen; Kristin Hegstad; Veli Mäkinen; Jukka Corander; Eva Heinz; Antti Honkela

doi:10.1099/mgen.0.000691

Bacterial Genomic Epidemiology with Mixed Samples

Tommi Mäklin, Teemu Kallonen, Jarno Alanko, Ørjan Samuelsen, Kristin Hegstad, Veli Mäkinen, Jukka Corander, Eva Heinz, Antti Honkela

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

Abstract

Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, opening the possibility to sequence all colonies on selective plates with a single DNA extraction and sequencing step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on single-colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.

Original language	English
Article number	000691
Journal	Microbial Genomics
Volume	7
Issue number	11
Number of pages	18
ISSN	2057-5858
DOIs	https://doi.org/10.1099/mgen.0.000691
Publication status	Published - 15 Nov 2021
MoE publication type	A1 Journal article-refereed

Fields of Science

ALGORITHM
CULTURE
DIVERSITY
EMERGENCE
ESCHERICHIA-COLI
METAGENOMICS
POPULATION-STRUCTURE
R PACKAGE
SINGLE-CELL
STRATEGIES
genomic epidemiology
pathogen surveillance
plate sweeps
probabilistic modelling
pseudoalignment
11832 Microbiology and virology
1184 Genetics, developmental biology, physiology

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10.1099/mgen.0.000691Licence: CC BY

bacterialFinal published version, 7.06 MBLicence: CC BY

Cite this

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title = "Bacterial Genomic Epidemiology with Mixed Samples",

abstract = "Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, opening the possibility to sequence all colonies on selective plates with a single DNA extraction and sequencing step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on single-colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.",

keywords = "ALGORITHM, CULTURE, DIVERSITY, EMERGENCE, ESCHERICHIA-COLI, METAGENOMICS, POPULATION-STRUCTURE, R PACKAGE, SINGLE-CELL, STRATEGIES, genomic epidemiology, pathogen surveillance, plate sweeps, probabilistic modelling, pseudoalignment, 11832 Microbiology and virology, 1184 Genetics, developmental biology, physiology",

author = "Tommi M{\"a}klin and Teemu Kallonen and Jarno Alanko and {\O}rjan Samuelsen and Kristin Hegstad and Veli M{\"a}kinen and Jukka Corander and Eva Heinz and Antti Honkela",

year = "2021",

month = nov,

day = "15",

doi = "10.1099/mgen.0.000691",

language = "English",

volume = "7",

journal = "Microbial Genomics",

issn = "2057-5858",

publisher = "American Society for Microbiology",

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T1 - Bacterial Genomic Epidemiology with Mixed Samples

AU - Mäklin, Tommi

AU - Kallonen, Teemu

AU - Alanko, Jarno

AU - Samuelsen, Ørjan

AU - Hegstad, Kristin

AU - Mäkinen, Veli

AU - Corander, Jukka

AU - Heinz, Eva

AU - Honkela, Antti

PY - 2021/11/15

Y1 - 2021/11/15

N2 - Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, opening the possibility to sequence all colonies on selective plates with a single DNA extraction and sequencing step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on single-colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.

AB - Genomic epidemiology is a tool for tracing transmission of pathogens based on whole-genome sequencing. We introduce the mGEMS pipeline for genomic epidemiology with plate sweeps representing mixed samples of a target pathogen, opening the possibility to sequence all colonies on selective plates with a single DNA extraction and sequencing step. The pipeline includes the novel mGEMS read binner for probabilistic assignments of sequencing reads, and the scalable pseudoaligner Themisto. We demonstrate the effectiveness of our approach using closely related samples in a nosocomial setting, obtaining results that are comparable to those based on single-colony picks. Our results lend firm support to more widespread consideration of genomic epidemiology with mixed infection samples.

KW - ALGORITHM

KW - CULTURE

KW - DIVERSITY

KW - EMERGENCE

KW - ESCHERICHIA-COLI

KW - METAGENOMICS

KW - POPULATION-STRUCTURE

KW - R PACKAGE

KW - SINGLE-CELL

KW - STRATEGIES

KW - genomic epidemiology

KW - pathogen surveillance

KW - plate sweeps

KW - probabilistic modelling

KW - pseudoalignment

KW - 11832 Microbiology and virology

KW - 1184 Genetics, developmental biology, physiology

UR - https://www.biorxiv.org/content/10.1101/2020.04.03.021501

U2 - 10.1099/mgen.0.000691

DO - 10.1099/mgen.0.000691

M3 - Article

VL - 7

JO - Microbial Genomics

JF - Microbial Genomics

SN - 2057-5858

IS - 11

M1 - 000691

ER -

Bacterial Genomic Epidemiology with Mixed Samples

Abstract

Fields of Science

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Finnish Grid Infrastructure

Mathematical and Statistical Aspects of Molecular Biology, 30 years edition

Eva Heinz

The 17th Bioinformatics Research and Education Workshop

Cite this

Bacterial Genomic Epidemiology with Mixed Samples

Abstract

Fields of Science

Access to Document

Other files and links

Equipment

Finnish Grid Infrastructure

Activities

Mathematical and Statistical Aspects of Molecular Biology, 30 years edition

Eva Heinz

The 17th Bioinformatics Research and Education Workshop

Cite this