Transcriptional Profiling of Pseudomonas aeruginosa Infections

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 largescale, 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.

Automated summary

This chapter reviews recent developments in transcriptional profiling of Pseudomonas aeruginosa infections and explains how advanced RNA-seq technology can provide new insights into the establishment and maintenance of these infections. It also discusses the use of large transcriptome datasets from clinical isolates to gain a greater understanding of bacterial adaptation during the infection process. Global genotype phenotype correlation studies have shed light on new evolutionary pathways and strategies used by P. aeruginosa to build a biofilm.