Pseudomonas aeruginosa transcriptome during human infection

Area of Science:

• Microbiology
• Infectious Diseases
• Genomics

Background:

• Extensive in vitro studies provide detailed bacterial physiology knowledge under lab conditions.
• Understanding bacterial behavior during human infections remains limited, despite environmental influences on bacterial growth.

Purpose of the Study:

• To compare the transcriptome of *Pseudomonas aeruginosa* during human infection with its transcriptome in various laboratory conditions.
• To identify gene expression differences that distinguish bacterial behavior in vivo from in vitro.

Main Methods:

• Transcriptome sequencing of *P. aeruginosa* from human infections and laboratory settings.
• Differential gene expression analysis.
• Application of support vector machines (machine learning) to classify transcriptomes.

Main Results:

• Significantly lower expression of primary quorum sensing systems in human infections compared to lab conditions.
• Substantially higher expression of antibiotic resistance genes during human infections.
• Identification of a gene set that reliably distinguishes in vitro from human infection transcriptomes.

Conclusions:

• Laboratory models do not fully replicate bacterial physiology during human infections.
• Discrepancies in gene expression, especially for antibiotic resistance, may explain underestimation of resistance in clinical settings.
• Developing more accurate models requires understanding differences between current lab systems and clinical infections.