In a clinical diagnosis microbiology laboratory, the current method of identifying bacterial isolates is based mainly on phenotypic characteristics, for example growth pattern on different media, colony morphology, Gram stain, and various biochemical reactions. These techniques collectively enable great accuracy in identifying most bacterial isolates, but are costly and time-consuming. In our clinical microbiology laboratory, we prospectively assessed the ability of matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) to identify bacterial strains that were routinely isolated from clinical samples. Bacterial colonies obtained from a total of 468 strains of 92 bacterial species isolated at the Department of Clinical Laboratory at Chiba University were directly placed on target MALDI plates followed by addition of CHCA matrix solution. The plates were then subjected to MALDI-TOF MS measurement and the microorganisms were identified by pattern matching with the libraries in the BioTyper 2.0 software. Identification success at the species and genus levels was 91.7% (429/468) and 97.0% (454/468), respectively. MALDI-TOF MS is a rapid, simple, and high-throughput proteomic technique for identification of a variety of bacterial species. Because colony-to-colony differences and effects of culture duration on the results are minimal, it can be implemented in a conventional laboratory setting. Although for some pathogens, preanalytical processes should be refined, and the current database should be improved to obtain more accurate results, the MALDI-TOF MS based method performs, in general, as well as conventional methods and is a promising technology in clinical laboratories.

Methicillin-resistant Staphylococcus aureus MRSA is one of the major pathogens responsible for nosocomial infections. The presence of MRSA in a hospital is detrimental to patients and to hospital management. Thus, rapid identification of MRSA is needed. Here, we report on a prospective method to rapidly discriminate of MSSA from MRSA using matrix-assisted laser desorption ionization-time of flight mass spectrometry MALDI-TOF MS and support vector machine SVM analysis in 160 clinical isolates of S. aureus. The predictive model was tested using 100 S. aureus isolates 50 MSSA and 50 MRSA . The identification rates were 90.0% for MSSA and 87.5% for MRSA in a 10-fold cross-validation SVM. In blind test sets, 60 S. aureus isolates 30 MSSA and 30 MRSA were correctly classified, with identification rates of 93.3% for MSSA and 86.7% for MRSA. The method proposed in this study using the predictive model enables detection of one colony in 5 minutes, and thus is useful at clinical sites at which rapid discrimination of MRSA from MSSA is required.Key words Rapid discrimination / MSSA / MRSA / MALDI-TOF MS / MALDI BioTyper software.

Methicillin-resistant coagulase-negative staphylococci were isolated from the nares and skin of 1-to 8-weekold healthy chickens in three flocks from a farm. Isolation of methicillin-resistant coagulase-negative staphylococci was positive for 72 (25.7%) of the 280 chickens tested, with the frequency varying from 2.2 to 100% according to flock. A total of 45 appropriate isolates were selected and subjected to identification. Of the 45 methicillin-resistant coagulase-negative staphylococcal isolates selected, 37 were identified as Staphylococcus sciuri, 5 were identified as Staphylococcus epidermidis, and 3 were identified as Staphylococcus saprophyticus. The distribution of the species was different among the flocks. Comparative analysis of the SmaI-digested chromosomal DNA by pulsed-field gel electrophoresis revealed that the isolates could have originated from a single clone of each of S. sciuri and S. saprophyticus and three clones of S. epidermidis. By two methods based on the PCR technique, the mecA gene was detected in all five representative isolates of each methicillin-resistant coagulase-negative staphylococcal clone. The nucleotide sequence of a PCR fragment obtained from an isolate of S. sciuri was completely identical to the corresponding region of mecA genes reported in human methicillinresistant Staphylococcus aureus isolates and Staphylococcus epidermidis isolates. The representative methicillinresistant coagulase-negative staphylococcal isolates were resistant to many ␤-lactam antibiotics, and some isolates were also resistant to macrolide and aminoglycoside antibiotics. This is the first evidence of the existence of methicillin-resistant coagulase-negative staphylococci from animals possessing the mecA gene.

17-Hydroxy docosahexaenoic acid (17-HDHA) is an oxidized form of docosahexaenoic acid (DHA) and known as a specialized proresolving mediator. We found that a further oxidized product, 17-oxodocosahexaenoic acid (17-oxoDHA), activates peroxisome proliferator-activated receptors γ (PPARγ) and PPARα in transcriptional assays and thus can be classified as an α/γ dual agonist. ESI mass spectroscopy and X-ray crystallographic analysis showed that 17-oxoDHA binds to PPARγ and PPARα covalently, making 17-oxoDHA the first of a novel class of PPAR agonists, the PPARα/γ dual covalent agonist. Furthermore, the covalent binding sites were identified as Cys285 for PPARγ and Cys275 for PPARα.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is increasingly used as a microbial diagnostic method for species identification of pathogens. However, MALDI-TOF identification of bacteria at the species level remains unsatisfactory, with the major problem being an incomplete database that still needs refinement and expansion. Augmentation of the original MALDI BioTyper 2.0 (Bruker) database by incorporating mass spectra obtained in-house from clinical isolates may increase the identification rate at the species level. We conducted a prospective study to assess whether the augmented database can improve the performance of MALDI-TOF MS for routine identification of species. Cluster analyses revealed distinct differences in MS spectral profiles of clinical isolates obtained in our hospital and those of ATCC strains in the Bruker database. In the first part of the study, which was performed over 3 weeks, 259 bacterial isolates were subjected to analysis by MALDI-TOF MS, and MS spectra of 229 successfully identified isolates (49 species) were incorporated into the original database to give the augmented Bruker-Chiba database. In a second separate analysis, the concordance of identification of 498 clinical isolates of the 49 species with conventional methods was 87.1% (434/498) with the commercial Bruker database and 98.0% (488/498) using the Bruker-Chiba database. These results indicate that refinement of a commercial database can be achieved relatively easy and effectively by incorporating MS spectra of clinical isolates obtained in a clinical laboratory.