Transcriptional profiling and metabolomic analysis of Staphylococcus aureus grown on autoclaved chicken breast.

Although Staphylococcus aureus is a major cause of food poisoning, little is known about its response to growth on food. Utilizing a transcriptional profiling and metabolomics approach, we compared S. aureus grown on autoclaved chicken breast (ACB) to Luria broth agar. ACB cultures demonstrated increased expression of genes associated with protein synthesis, cofactors, secondary metabolites, nitrogen and nucleotide metabolism, amino acid transport, and reduced expression of general stress, lipid metabolism, and virulence genes. The ACB culture also displayed characteristics of catabolite de-repression and anaerobic growth, and increased expression of arginine biosynthesis genes (argFGH) and an arginine/ornithine antiporter gene (arcD). S. aureus synthesizes arginine from proline and the ACB culture exhibited increased expression of proline transport genes (opuBA, opuBB and putP) and increased proline accumulation. Amino acid and sugar content in the ACB grown culture increased, and this was attributed to the consumption of ACB, transport of amino acids, and gluconeogenesis. Genes involved with biotin biosynthesis and uptake were upregulated and biotin is required for amino acid catabolism. Genes encoding urease and urease activity were upregulated in ACB cultures, while urea levels were reduced. This research provides fundamental information on the response of S. aureus growing on chicken meat that could find application in future attempts to reduce the growth of S. aureus in food.

Proof of Principle for a Real-Time Pathogen Isolation Media Diagnostic: The Use of Laser-Induced Breakdown Spectroscopy to Discriminate Bacterial Pathogens and Antimicrobial-Resistant Staphylococcus aureus Strains Grown on Blood Agar.

Laser-Induced Breakdown Spectroscopy (LIBS) is a rapid, in situ, diagnostic technique in which light emissions from a laser plasma formed on the sample are used for analysis allowing automated analysis results to be available in seconds to minutes. This speed of analysis coupled with little or no sample preparation makes LIBS an attractive detection tool. In this study, it is demonstrated that LIBS can be utilized to discriminate both the bacterial species and strains of bacterial colonies grown on blood agar. A discrimination algorithm was created based on multivariate regression analysis of spectral data. The algorithm was deployed on a simulated LIBS instrument system to demonstrate discrimination capability using 6 species. Genetically altered Staphylococcus aureus strains grown on BA, including isogenic sets that differed only by the acquisition of mutations that increase fusidic acid or vancomycin resistance, were also discriminated. The algorithm successfully identified all thirteen cultures used in this study in a time period of 2 minutes. This work provides proof of principle for a LIBS instrumentation system that could be developed for the rapid discrimination of bacterial species and strains demonstrating relatively minor genomic alterations using data collected directly from pathogen isolation media.

Alterations in the transcriptome and antibiotic susceptibility of Staphylococcus aureus grown in the presence of diclofenac.

BACKGROUND: Diclofenac is a non-steroidal anti-inflammatory drug (NSAID) which has been shown to increase the susceptibility of various bacteria to antimicrobials and demonstrated to have broad antimicrobial activity. This study describes transcriptome alterations in S. aureus strain COL grown with diclofenac and characterizes the effects of this NSAID on antibiotic susceptibility in laboratory, clinical and diclofenac reduced-susceptibility (DcRS) S. aureus strains. METHODS: Transcriptional alterations in response to growth with diclofenac were measured using S. aureus gene expression microarrays and quantitative real-time PCR. Antimicrobial susceptibility was determined by agar diffusion MICs and gradient plate analysis. Ciprofloxacin accumulation was measured by fluorescence spectrophotometry. RESULTS: Growth of S. aureus strain COL with 80 µg/ml (0.2 × MIC) of diclofenac resulted in the significant alteration by ≥2-fold of 458 genes. These represented genes encoding proteins for transport and binding, protein and DNA synthesis, and the cell envelope. Notable alterations included the strong down-regulation of antimicrobial efflux pumps including mepRAB and a putative emrAB/qacA-family pump. Diclofenac up-regulated sigB (σB), encoding an alternative sigma factor which has been shown to be important for antimicrobial resistance. Staphylococcus aureus microarray metadatabase (SAMMD) analysis further revealed that 46% of genes differentially-expressed with diclofenac are also σB-regulated. Diclofenac altered S. aureus susceptibility to multiple antibiotics in a strain-dependent manner. Susceptibility increased for ciprofloxacin, ofloxacin and norfloxacin, decreased for oxacillin and vancomycin, and did not change for tetracycline or chloramphenicol. Mutation to DcRS did not affect susceptibility to the above antibiotics. Reduced ciprofloxacin MICs with diclofenac in strain BB255, were not associated with increased drug accumulation. CONCLUSIONS: The results of this study suggest that diclofenac influences antibiotic susceptibility in S. aureus, in part, by altering the expression of regulatory and structural genes associated with cell wall biosynthesis/turnover and transport.

The use of laser-induced breakdown spectroscopy for distinguishing between bacterial pathogen species and strains.

Laser-induced breakdown spectroscopy (LIBS) was used in a blind study to successfully differentiate bacterial pathogens, both species and strain. The pathogens used for the study were chosen and prepared by one set of researchers. The LIBS data were collected and analyzed by another set of researchers. The latter researchers had no knowledge of the sample identities other than that (1) the first five of fifteen samples were unique (not replicates) and (2) the remaining ten samples consisted of two replicates of each of the first five samples. Using only chemometric analysis of the LIBS data, the ten replicate bacterial samples were successfully matched to each of the first five samples. The results of this blind study show it is possible to differentiate the bacterial pathogens Escherichia coli, three clonal methicillin-resistant Staphylococcus aureus (MRSA) strains, and one unrelated MRSA strain using LIBS. This is an important finding because it demonstrates that LIBS can be used to determine bacterial pathogen species within a defined sample set and can be used to differentiate between clonal relationships among strains of a single multiple-antibiotic-resistant bacterial species. Such a capability is important for the development of LIBS instruments for use in medical, water, and food safety applications.