Inferring bacterial transmission dynamics using deep sequencing genomic surveillance data.


Journal

Nature communications
ISSN: 2041-1723
Titre abrégé: Nat Commun
Pays: England
ID NLM: 101528555

Informations de publication

Date de publication:
31 10 2023
Historique:
received: 13 11 2022
accepted: 27 09 2023
medline: 2 11 2023
pubmed: 1 11 2023
entrez: 1 11 2023
Statut: epublish

Résumé

Identifying and interrupting transmission chains is important for controlling infectious diseases. One way to identify transmission pairs - two hosts in which infection was transmitted from one to the other - is using the variation of the pathogen within each single host (within-host variation). However, the role of such variation in transmission is understudied due to a lack of experimental and clinical datasets that capture pathogen diversity in both donor and recipient hosts. In this work, we assess the utility of deep-sequenced genomic surveillance (where genomic regions are sequenced hundreds to thousands of times) using a mouse transmission model involving controlled spread of the pathogenic bacterium Citrobacter rodentium from infected to naïve female animals. We observe that within-host single nucleotide variants (iSNVs) are maintained over multiple transmission steps and present a model for inferring the likelihood that a given pair of sequenced samples are linked by transmission. In this work we show that, beyond the presence and absence of within-host variants, differences arising in the relative abundance of iSNVs (allelic frequency) can infer transmission pairs more precisely. Our approach further highlights the critical role bottlenecks play in reserving the within-host diversity during transmission.

Identifiants

pubmed: 37907520
doi: 10.1038/s41467-023-42211-8
pii: 10.1038/s41467-023-42211-8
pmc: PMC10618251
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

6397

Informations de copyright

© 2023. Springer Nature Limited.

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Auteurs

Madikay Senghore (M)

Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA. msenghore@hsph.harvard.edu.

Hannah Read (H)

Bioluminescent Superbugs Lab, Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand.

Priyali Oza (P)

Bioluminescent Superbugs Lab, Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand.

Sarah Johnson (S)

Bioluminescent Superbugs Lab, Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand.

Hemanoel Passarelli-Araujo (H)

Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.
Department of Biochemistry and Immunology, Federal University of Minas Gerais, Minas Gerais, Brazil.

Bradford P Taylor (BP)

Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.

Stephen Ashley (S)

Bioluminescent Superbugs Lab, Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand.

Alex Grey (A)

Bioluminescent Superbugs Lab, Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand.

Alanna Callendrello (A)

Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.

Robyn Lee (R)

Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.
University of Toronto Dalla Lana School of Public Health, Toronto, ON, Canada.

Matthew R Goddard (MR)

School of Biological Sciences, University of Auckland, Auckland, New Zealand.
School of Life and Environmental Sciences, University of Lincoln, Lincoln, UK.

Thomas Lumley (T)

Department of Statistics, University of Auckland, Auckland, New Zealand.

William P Hanage (WP)

Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA.

Siouxsie Wiles (S)

Bioluminescent Superbugs Lab, Department of Molecular Medicine and Pathology, University of Auckland, Auckland, New Zealand. s.wiles@auckland.ac.nz.
Te Pūnaha Matatini, Centre of Research Excellence in Complex Systems, Auckland, New Zealand. s.wiles@auckland.ac.nz.

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