Figure 2.

Multiscale analysis identifies within-host metabolic modifications of P.a associated with the acquisition of beta-lactam resistances. (a) Schematic summary of untargeted LC-HRMS metabolomic analysis workflow for acquisition of P.a isolates’ metabolic profiles. (b) Intra-host modifications between early and late isolates from 33 evolutive lines have been assessed by calculating the P_i,j value for each line i, metabolite or resistance phenotype j. (c) Distributions of metabolite P_i,j representing intra-host modifications of 271 annotated metabolite intensities. (d) Hierarchical cluster analysis of antibiotic resistance P_i,j representing intra-host modifications of resistance against 14 antibiotics (*). (e) Multiscale data integration workflow for the identification of metabolic signatures associated with the acquisition of antibiotic resistance: (i) unsupervised HCPC identified 3 clusters of P.a lines with similar modifications of both antibiotic resistances and metabolite intensities; (ii) cluster 1 (in red) is significantly associated with acquisition of antibiotic resistances, especially against beta-lactams (χ2 p-value < 0.05), and with modifications in the abundance of 5 metabolites; (iii) selection of significantly associated metabolites and antibiotics to build a supervised logistic model predicting acquisition of antibiotic resistances from metabolic changes; (f) cross-validation of the best logistic regression model, which predicts the acquisition of beta-lactam resistance from an increased production of Ala-Glu-meso-diaminopimelate. ** p-values < 0.01. (*) abbreviations: FQ: fluoroquinolones; AKN: amikacin, ATM: aztreonam, CIP: ciprofloxacin, CZD: ceftazidime, FEP: cefepime, GMN: gentamicin, IPM: imipenem, LVX: levofloxacin, MEM: meropenem, PIL: piperacillin, PTZ: piperacillin-tazobactam, TCC: ticarcillin-clavulanic acid, TIC: ticarcillin, TMN: tobramycin.