Evolutionary highways to persistent bacterial infection

Jennifer Bartell*, Lea M. Sommer, Janus Anders Juul Haagensen, Anne Loch, Rocio Espinosa Portero, Søren Molin, Helle Krogh Johansen

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Persistent infections require bacteria to evolve from their naive colonization state by optimizing fitness in the host via simultaneous adaptation of multiple traits, which can obscure evolutionary trends and complicate infection management. Accordingly, here we screen 8 infection-relevant phenotypes of 443 longitudinal Pseudomonas aeruginosa isolates from 39 young cystic fibrosis patients over 10 years. Using statistical modeling, we map evolutionary trajectories and identify trait correlations accounting for patient-specific influences. By integrating previous genetic analyses of 474 isolates, we provide a window into early adaptation to the host, finding: (1) a 2-3 year timeline of rapid adaptation after colonization, (2) variant "naive" and "adapted" states reflecting discordance between phenotypic and genetic adaptation, (3) adaptive trajectories leading to persistent infection via three distinct evolutionary modes, and (4) new associations between phenotypes and pathoadaptive mutations. Ultimately, we effectively deconvolute complex trait adaptation, offering a framework for evolutionary studies and precision medicine in clinical microbiology.
Original languageEnglish
Article number629
JournalNature Communications
Volume10
Number of pages13
ISSN2041-1723
DOIs
Publication statusPublished - 2019

Keywords

  • Evolutionary genetics
  • Evolvability
  • Microbial ecology
  • Pathogens

Cite this

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title = "Evolutionary highways to persistent bacterial infection",
abstract = "Persistent infections require bacteria to evolve from their naive colonization state by optimizing fitness in the host via simultaneous adaptation of multiple traits, which can obscure evolutionary trends and complicate infection management. Accordingly, here we screen 8 infection-relevant phenotypes of 443 longitudinal Pseudomonas aeruginosa isolates from 39 young cystic fibrosis patients over 10 years. Using statistical modeling, we map evolutionary trajectories and identify trait correlations accounting for patient-specific influences. By integrating previous genetic analyses of 474 isolates, we provide a window into early adaptation to the host, finding: (1) a 2-3 year timeline of rapid adaptation after colonization, (2) variant {"}naive{"} and {"}adapted{"} states reflecting discordance between phenotypic and genetic adaptation, (3) adaptive trajectories leading to persistent infection via three distinct evolutionary modes, and (4) new associations between phenotypes and pathoadaptive mutations. Ultimately, we effectively deconvolute complex trait adaptation, offering a framework for evolutionary studies and precision medicine in clinical microbiology.",
keywords = "Evolutionary genetics, Evolvability, Microbial ecology, Pathogens",
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language = "English",
volume = "10",
journal = "Nature Communications",
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}

Evolutionary highways to persistent bacterial infection. / Bartell, Jennifer; Sommer, Lea M.; Haagensen, Janus Anders Juul; Loch, Anne; Espinosa Portero, Rocio; Molin, Søren; Johansen, Helle Krogh.

In: Nature Communications, Vol. 10, 629, 2019.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Evolutionary highways to persistent bacterial infection

AU - Bartell, Jennifer

AU - Sommer, Lea M.

AU - Haagensen, Janus Anders Juul

AU - Loch, Anne

AU - Espinosa Portero, Rocio

AU - Molin, Søren

AU - Johansen, Helle Krogh

PY - 2019

Y1 - 2019

N2 - Persistent infections require bacteria to evolve from their naive colonization state by optimizing fitness in the host via simultaneous adaptation of multiple traits, which can obscure evolutionary trends and complicate infection management. Accordingly, here we screen 8 infection-relevant phenotypes of 443 longitudinal Pseudomonas aeruginosa isolates from 39 young cystic fibrosis patients over 10 years. Using statistical modeling, we map evolutionary trajectories and identify trait correlations accounting for patient-specific influences. By integrating previous genetic analyses of 474 isolates, we provide a window into early adaptation to the host, finding: (1) a 2-3 year timeline of rapid adaptation after colonization, (2) variant "naive" and "adapted" states reflecting discordance between phenotypic and genetic adaptation, (3) adaptive trajectories leading to persistent infection via three distinct evolutionary modes, and (4) new associations between phenotypes and pathoadaptive mutations. Ultimately, we effectively deconvolute complex trait adaptation, offering a framework for evolutionary studies and precision medicine in clinical microbiology.

AB - Persistent infections require bacteria to evolve from their naive colonization state by optimizing fitness in the host via simultaneous adaptation of multiple traits, which can obscure evolutionary trends and complicate infection management. Accordingly, here we screen 8 infection-relevant phenotypes of 443 longitudinal Pseudomonas aeruginosa isolates from 39 young cystic fibrosis patients over 10 years. Using statistical modeling, we map evolutionary trajectories and identify trait correlations accounting for patient-specific influences. By integrating previous genetic analyses of 474 isolates, we provide a window into early adaptation to the host, finding: (1) a 2-3 year timeline of rapid adaptation after colonization, (2) variant "naive" and "adapted" states reflecting discordance between phenotypic and genetic adaptation, (3) adaptive trajectories leading to persistent infection via three distinct evolutionary modes, and (4) new associations between phenotypes and pathoadaptive mutations. Ultimately, we effectively deconvolute complex trait adaptation, offering a framework for evolutionary studies and precision medicine in clinical microbiology.

KW - Evolutionary genetics

KW - Evolvability

KW - Microbial ecology

KW - Pathogens

U2 - 10.1038/s41467-019-08504-7

DO - 10.1038/s41467-019-08504-7

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JO - Nature Communications

JF - Nature Communications

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ER -