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An integrated model system to gain mechanistic insights into biofilm formation and antimicrobial resistance development in Pseudomonas aeruginosa MPAO1

An integrated model system to gain mechanistic insights into biofilm formation and antimicrobial resistance development in Pseudomonas aeruginosa MPAO1
An integrated model system to gain mechanistic insights into biofilm formation and antimicrobial resistance development in Pseudomonas aeruginosa MPAO1
Pseudomonas aeruginosa MPAO1 is the parental strain of the widely utilized transposon mutant collection for this important clinical pathogen. Here, we validate a model system to identify genes involved in biofilm growth and antibiotic resistance.

Our model employs a genomics-driven workflow to assemble the complete MPAO1 genome, identify unique and conserved genes by comparative genomics with the PAO1 reference strain and missed genes by proteogenomics. Among over 200 unique MPAO1 genes, we identified six general essential genes that were overlooked when mapping public Tn-seq datasets against PAO1, including an antitoxin. Genomic data were integrated with phenotypic data from an experimental workflow using a user-friendly, soft lithography-based microfluidic flow chamber for biofilm growth. Experiments conducted across three laboratories delivered reproducible data on P. aeruginosa biofilms and validated both known and novel genes involved in biofilm growth and antibiotic resistance identified in screens of the mutant collection. Differential protein expression data from planktonic cells versus biofilm confirmed upregulation of candidates known to affect biofilm formation, of structural and secreted proteins of type six secretion systems, and provided proteogenomic evidence for some missed MPAO1 genes. This integrated, broadly applicable model promises to improve the mechanistic understanding of biofilm formation, antimicrobial tolerance and resistance evolution.
Varadarajan, Adithi R.
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Allan, Raymond N.
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Valentin, Jules D.P.
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Castañeda Ocampo, Olga E.
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Somerville, Vincent
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Pietsch, Franziska
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Buhmann, Matthias T.
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West, Jonathan
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Skipp, Paul J.
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Van der Mei, Henny C.
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Ren, Qun
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Schreiber, Frank
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Webb, Jeremy S.
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Ahrens, Christian H.
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Varadarajan, Adithi R.
ff277cc5-a4fc-46cd-9410-fda3a909b017
Allan, Raymond N.
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Valentin, Jules D.P.
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Castañeda Ocampo, Olga E.
6fab38dc-e991-4de5-8aff-48282c4ce935
Somerville, Vincent
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Pietsch, Franziska
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Buhmann, Matthias T.
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West, Jonathan
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Skipp, Paul J.
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Van der Mei, Henny C.
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Ren, Qun
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Schreiber, Frank
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Webb, Jeremy S.
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Ahrens, Christian H.
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Varadarajan, Adithi R., Allan, Raymond N., Valentin, Jules D.P., Castañeda Ocampo, Olga E., Somerville, Vincent, Pietsch, Franziska, Buhmann, Matthias T., West, Jonathan, Skipp, Paul J., Van der Mei, Henny C., Ren, Qun, Schreiber, Frank, Webb, Jeremy S. and Ahrens, Christian H. (2020) An integrated model system to gain mechanistic insights into biofilm formation and antimicrobial resistance development in Pseudomonas aeruginosa MPAO1. NPJ Biofilms and Microbiomes, 6 (46). (doi:10.1101/2020.02.06.936690).

Record type: Article

Abstract

Pseudomonas aeruginosa MPAO1 is the parental strain of the widely utilized transposon mutant collection for this important clinical pathogen. Here, we validate a model system to identify genes involved in biofilm growth and antibiotic resistance.

Our model employs a genomics-driven workflow to assemble the complete MPAO1 genome, identify unique and conserved genes by comparative genomics with the PAO1 reference strain and missed genes by proteogenomics. Among over 200 unique MPAO1 genes, we identified six general essential genes that were overlooked when mapping public Tn-seq datasets against PAO1, including an antitoxin. Genomic data were integrated with phenotypic data from an experimental workflow using a user-friendly, soft lithography-based microfluidic flow chamber for biofilm growth. Experiments conducted across three laboratories delivered reproducible data on P. aeruginosa biofilms and validated both known and novel genes involved in biofilm growth and antibiotic resistance identified in screens of the mutant collection. Differential protein expression data from planktonic cells versus biofilm confirmed upregulation of candidates known to affect biofilm formation, of structural and secreted proteins of type six secretion systems, and provided proteogenomic evidence for some missed MPAO1 genes. This integrated, broadly applicable model promises to improve the mechanistic understanding of biofilm formation, antimicrobial tolerance and resistance evolution.

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2020.02.06.936690v1.full - Author's Original
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More information

Accepted/In Press date: 7 February 2020
e-pub ahead of print date: 30 October 2020
Published date: 2020

Identifiers

Local EPrints ID: 439564
URI: http://eprints.soton.ac.uk/id/eprint/439564
PURE UUID: 6403ff1c-0cea-499d-83c5-aa04f0d3c8a6
ORCID for Jonathan West: ORCID iD orcid.org/0000-0002-5709-6790
ORCID for Paul J. Skipp: ORCID iD orcid.org/0000-0002-2995-2959
ORCID for Jeremy S. Webb: ORCID iD orcid.org/0000-0003-2068-8589

Catalogue record

Date deposited: 27 Apr 2020 16:30
Last modified: 17 Mar 2024 03:29

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Contributors

Author: Adithi R. Varadarajan
Author: Raymond N. Allan
Author: Jules D.P. Valentin
Author: Olga E. Castañeda Ocampo
Author: Vincent Somerville
Author: Franziska Pietsch
Author: Matthias T. Buhmann
Author: Jonathan West ORCID iD
Author: Paul J. Skipp ORCID iD
Author: Henny C. Van der Mei
Author: Qun Ren
Author: Frank Schreiber
Author: Jeremy S. Webb ORCID iD
Author: Christian H. Ahrens

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