Literature DB >> 36258077

Transcriptional Profiling of Pseudomonas aeruginosa Infections.

Janne G Thöming1,2, Susanne Häussler3,4,5,6.   

Abstract

Pseudomonas aeruginosa is an opportunistic pathogen that causes life-devastating acute as well as chronic biofilm-associated infections with limited treatment options. Its success is largely due to its remarkable adaptability. P. aeruginosa uses different long- and short-term adaptive mechanisms to increase its fitness, both at the population level through genetic diversification and at the individual cell level by adapting gene expression. These adapted gene expression profiles can be fixed by the accumulation of patho-adaptive mutations. The latter are often found in transcriptional regulators and lead to rewiring of the regulatory network to promote survival at the infected host site. In this chapter, we review recent developments in transcriptional profiling and explain how these provide new insights into the establishment and maintenance of P. aeruginosa infections. We illustrate what can be learned from the application of advanced RNA-seq technology, such as ex vivo RNA-seq, host-pathogen crosstalk (dual RNA-seq), or recording of transcriptional heterogeneity within a bacterial population (single-cell RNA-seq). In addition, we discuss how large transcriptome datasets from a variety of clinical isolates can be used to gain an expanded understanding of bacterial adaptation during the infection process. Global genotype-phenotype correlation studies provide a unique opportunity to discover new evolutionary pathways of infection-related phenotypes and led to the discovery of different strategies of the pathogen P. aeruginosa to build a biofilm. Insights gained from large-scale, multi-layered functional -omics approaches will continue to contribute to a more comprehensive understanding of P. aeruginosa adaptation to the host habitat and promises to pave the way for novel strategies to combat recalcitrant infections.
© 2022. The Author(s), under exclusive license to Springer Nature Switzerland AG.

Entities:  

Keywords:  Adaptation; Biofilm formation; Genotype–phenotype correlation; Pseudomonas aeruginosa; Transcriptional profiling

Mesh:

Year:  2022        PMID: 36258077     DOI: 10.1007/978-3-031-08491-1_11

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   3.650


  133 in total

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Authors:  Deepak Balasubramanian; Lisa Schneper; Hansi Kumari; Kalai Mathee
Journal:  Nucleic Acids Res       Date:  2012-11-11       Impact factor: 16.971

8.  Identification of FDA-approved antivirulence drugs targeting the Pseudomonas aeruginosa quorum sensing effector protein PqsE.

Authors:  Valerio Baldelli; Francesca D'Angelo; Viola Pavoncello; Ersilia Vita Fiscarelli; Paolo Visca; Giordano Rampioni; Livia Leoni
Journal:  Virulence       Date:  2020-12       Impact factor: 5.882

9.  Prokaryotic single-cell RNA sequencing by in situ combinatorial indexing.

Authors:  Sydney B Blattman; Wenyan Jiang; Panos Oikonomou; Saeed Tavazoie
Journal:  Nat Microbiol       Date:  2020-05-25       Impact factor: 17.745

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Authors:  Matthew T Cabeen
Journal:  PLoS One       Date:  2014-02-12       Impact factor: 3.240

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