BackgroundThe emergence of antibiotic resistant pathogenic bacteria has reduced our ability to combat infectious diseases. At the same time the numbers of new antibiotics reaching the market have decreased. This situation has created an urgent need to discover novel antibiotic scaffolds. Recently, the application of pattern recognition techniques to identify molecular fingerprints in ‘omics’ studies, has emerged as an important tool in biomedical research and laboratory medicine to identify pathogens, to monitor therapeutic treatments or to develop drugs with improved metabolic stability, toxicological profile and efficacy. Here, we hypothesize that a combination of metabolic intracellular fingerprints and extracellular footprints would provide a more comprehensive picture about the mechanism of action of novel antibiotics in drug discovery programs.ResultsIn an attempt to integrate the metabolomics approach as a classification tool in the drug discovery processes, we have used quantitative 1H NMR spectroscopy to study the metabolic response of Escherichia coli cultures to different antibiotics. Within the frame of our study the effects of five different and well-known antibiotic classes on the bacterial metabolome were investigated both by intracellular fingerprint and extracellular footprint analysis. The metabolic fingerprints and footprints of bacterial cultures were affected in a distinct manner and provided complementary information regarding intracellular and extracellular targets such as protein synthesis, DNA and cell wall. While cell cultures affected by antibiotics that act on intracellular targets showed class-specific fingerprints, the metabolic footprints differed significantly only when antibiotics that target the cell wall were applied. In addition, using a training set of E. coli fingerprints extracted after treatment with different antibiotic classes, the mode of action of streptomycin, tetracycline and carbenicillin could be correctly predicted.ConclusionThe metabolic profiles of E. coli treated with antibiotics with intracellular and extracellular targets could be separated in fingerprint and footprint analysis, respectively and provided complementary information. Based on the specific fingerprints obtained for different classes of antibiotics, the mode of action of several antibiotics could be predicted. The same classification approach should be applicable to studies of other pathogenic bacteria.

Aspergillus fumigatus is an opportunistic human pathogenic fungus causing severe infections in immunocompromised patients. Cyclic AMP (cAMP) signal transduction plays an important role in virulence. A central component of this signaling cascade is protein kinase A (PKA), which regulates cellular processes by phosphorylation of specific target proteins. Here we describe the generation and analysis of A. fumigatus mutants expressing the gene encoding the catalytic subunit of PKA, pkaC1, under control of an inducible promoter. Strains overexpressing pkaC1 showed high PKA activity, reduced growth, sporulation deficiency, and formation of a dark pigment in the mycelium. These data indicate that cAMP-PKA signaling is involved in the regulation of important processes, such as growth, asexual reproduction, and biosynthesis of secondary metabolites. Furthermore, elevated PKA activity led to increased expression of the pksP gene. The polyketide synthase PksP is an essential enzyme for production of dihydroxynaphthalene-melanin in A. fumigatus and contributes to virulence. Our results suggest that increased pksP expression is responsible for pigment formation in the mycelium. Comparative proteome analysis of the pkaC1-overexpressing strain and the wild-type strain led to the identification of proteins regulated by the cAMP-PKA signal transduction pathway. We showed that elevated PKA activity resulted in activation of stress-associated proteins and of enzymes involved in protein biosynthesis and glucose catabolism. In contrast, proteins which were involved in nucleotide and amino acid biosynthesis were downregulated, as were enzymes involved in catabolism of carbon sources other than glucose.

The purpose of this study was to prospectively evaluate the diagnostic accuracy of reader detection of 75% or greater stenosis at high-spatial-resolution multistation magnetic resonance (MR) angiography performed with matrix coils and a blood pool contrast agent. Ten healthy volunteers and 10 patients were examined. All participants provided informed consent to participate in this institutional review board-approved study. For contrast agent-enhanced multistation MR angiography, an albumin-binding gadolinium chelate, gadofosveset trisodium, was used. Imaging was performed during the first-pass and steady-state phases of the contrast agent. Vessel conspicuity on the first-pass MR angiograms obtained in both volunteers and patients was rated as excellent for 93% of vessels. At steady-state imaging, vessel conspicuity was rated as excellent or good for 89% of vessels. Gadofosveset trisodium-enhanced MR angiography yielded sensitivities of 100% and 97% and specificities of 96% and 97% for detection of significant disease in the carotid and lower extremity arteries, respectively.

Single cell analysis is an emerging field requiring a high level interdisciplinary collaboration to provide detailed insights into the complex organisation, function and heterogeneity of life. This review is addressed to life science researchers as well as researchers developing novel technologies. It covers all aspects of the characterisation of single cells (with a special focus on mammalian cells) from morphology to genetics and different omics-techniques to physiological, mechanical and electrical methods. In recent years, tremendous advances have been achieved in all fields of single cell analysis: (1) improved spatial and temporal resolution of imaging techniques to enable the tracking of single molecule dynamics within single cells; (2) increased throughput to reveal unexpected heterogeneity between different individual cells raising the question what characterizes a cell type and what is just natural biological variation; and (3) emerging multimodal approaches trying to bring together information from complementary techniques paving the way for a deeper understanding of the complexity of biological processes. This review also covers the first successful translations of single cell analysis methods to diagnostic applications in the field of tumour research (especially circulating tumour cells), regenerative medicine, drug discovery and immunology.