Life-long bacterial infections in cystic fibrosis (CF) airways constitute an excellent model both for persistent infections and for microbial adaptive evolution in complex dynamic environments. Using high-resolution transcriptomics applied on CF sputum, we profile transcriptional phenotypes of Pseudomonas aeruginosa populations in patho-physiological conditions. Here we show that the soft-core genome of genetically distinct populations, while maintaining transcriptional flexibility, shares a common expression program tied to the lungs environment. We identify genetically independent traits defining P. aeruginosa physiology in vivo, documenting the connection between several previously identified mutations in CF isolates and some of the convergent phenotypes known to develop in later stages of the infection. In addition, our data highlight to what extent this organism can exploit its extensive repertoire of physiological pathways to acclimate to a new niche and suggest how alternative nutrients produced in the lungs may be utilized in unexpected metabolic contexts.