A clonal strain of Klebsiella pneumoniae producing the plasmid-encoded cephalosporinase DHA-1 was isolated from four patients admitted to the teaching hospital of Clermont-Ferrand, France, in 2006. It was responsible for severe infections in three of the patients; the fourth was colonized only in the gastrointestinal tract. The strain had at least two plasmids encoding resistance to antibiotics (quinolones, aminoglycosides, chloramphenicol, sulfonamides, and trimethoprim), as shown by disk diffusion assay, and harbored only a few genes for virulence factors (wabG and mrkD), as shown by PCRs. DHA-1 synthesis is regulated by an upstream, divergently transcribed gene, ampR, which is also involved in the expression of virulence factors in Pseudomonas aeruginosa. To investigate the role of AmpR in K. pneumoniae, we cloned the wild-type ampR gene from the DHA-1 clonal isolate into a previously characterized K. pneumoniae background plasmid-cured strain, CH608. ampR was also introduced into a CH608 isogenic mutant deleted of ampD, in which AmpR is present only in its activator form, resulting in constitutive hyperproduction of the ␤-lactamase. We showed that ampR was involved in the upregulation of capsule synthesis and therefore in resistance to killing by serum. AmpR also modulated biofilm formation and type 3 fimbrial gene expression, as well as colonization of the murine gastrointestinal tract and adhesion to HT-29 intestinal epithelial cells. These results show the pleiotropic role of ampR in the pathogenesis process of K. pneumoniae.

We show here that matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) accurately and quickly identified the five high-risk clones of Pseudomonas aeruginosa sequence type 111 (ST111), ST175, ST235, ST253, and ST395. The use of this screening technique by clinical microbiology laboratories may tackle the spread of high-risk clones by the quick implementation of hygiene control procedures for relevant patients. Pseudomonas aeruginosa has a nonclonal population structure with a few multidrug-resistant clusters, called "high-risk clones," that frequently produce acquired ␤-lactamases with an extended spectrum and are responsible for outbreaks in hospitals worldwide (1-13). The quick implementation of infection control measures for relevant patients may tackle the spread of these epidemic clones, but current identification is long and complex since it is based on the analysis of nucleotidic sequences. A quick and easy method for identifying high-risk clones of P. aeruginosa is then needed. Matrixassisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) was recently integrated into the routine workflow of medical microbiology laboratories for microbial identification and has been further used for subspecies characterization (14). Here, we evaluated the ability of MALDI-TOF MS to identify high-risk clones of P. aeruginosa.Identification of peak biomarkers for five major high-risk clones of P. aeruginosa. In order to identify five major high-risk clones of P. aeruginosa (sequence type 111 [ST111], ST175, ST235, ST253, and ST395), we first defined recognition models with a training set of 46 isolates with known STs distributed homogeneously in the phylogenetic tree (Table 1 and Fig. 1). Frozen bacteria were streaked onto Mueller-Hinton agar (Bio-Rad) and incubated for 18 h at 37°C. As previously reported (15), each isolate was extracted with the ethanol-formic acid method recommended by Bruker Daltonik and analyzed with a Microflex LT mass spectrometer (Bruker Daltonik), which generated 24 raw spectra. We analyzed the spectra with the software ClinProTools 3.0 (Bruker Daltonik), which defined six models based on peak biomarkers (Table 1). The reliability and accuracy of each model were assessed through the recognition capabilities and the crossvalidation values. The models identified all the tested high-risk clones of P. aeruginosa with high recognition capabilities (Ͼ96%) and cross-validation values ranging from 72.5% to 100% (Table 1). Four models directly identified ST111, ST175, ST253, and ST395, while the identification of ST235 required a preliminary stage to identify cluster 1, which encompasses ST235 (Fig. 1).We then manually examined the spectra with ClinProTools 3.0 to assess the relevance of the peak biomarkers of each model (Table 1). Peaks were defined as biomarkers in a model because of their presence or absence or relative abundance between two tested classes. Figure 2 details only the peak biomarkers in which presence or absence was specif...

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