CE-ESI-MS metabolic fingerprinting of Leishmania resistance to antimony treatment

Metabolomics has become an invaluable tool to unveil biology of pathogens, with immediate application to chemotherapy. It is currently accepted that there is not one single technique capable of obtaining the whole metabolic fingerprint of a biological system either due to their different physical-chemical properties or concentrations. In this work, we have explored the capability of capillary electrophoresis mass spectrometry with a sheathless interface with electrospray ionization (CE-ESI-TOF-MS) to separate metabolites in order to be used as a complementary technique to LC. As proof of concept, we have compared the metabolome of Leishmania infantum promastigotes BCN 150 (Sb (III) IC50 = 20.9 mu M) and its variation when treated with 120 mu M of Sb(III) potassium tartrate for 12 h, as well as with its Sb(III) resistant counterpart obtained by growth of the parasites under increasing Sb(III) in a step-wise manner up to 180 mu M. The number of metabolites compared were of 264 for BCN150 Sb(III) treated versus nontreated and of 195 for Sb(III) resistant versus susceptible parasites. After successive data filtering, differences in seven metabolites identified in databases for Leishmania pathways, showed the highest significant differences, corresponding mainly to amino acids or their metabolite surrogates. Most of them were assigned to sulfur containing amino acids and polyamine biosynthetic pathways, of special relevance considering the deterioration of the thiol-dependent redox metabolism in Leishmania by Sb(III). Given the low concentrations typical for most of these metabolites, the assay can be considered a success that should be explored for new biological questions.

Electrospray Ionization Mass Spectrometry Fingerprinting of Extracts of the Leaves of Arrabidaea chica

Arrabidaea chica (crajiru) is an important Amazonian plant. Its extracts are used as red pigments, antimicrobial agents and astringents. Three different varieties of this species are cultivated in the Amazon region. In this work, direct infusions of A. chica extracts from these three varieties were analyzed via electrospray ionization mass spectrometry (ESI(+)-MS) fingerprinting. Derived data from the spectra were classified by using a multivariate method (PLS-DA, partial least squares-discriminant analysis). The direct method that is herein presented relies on extraction of dry, powdered leaves with acidified methanol/water solution with no further sample preparation. The resulting supernatants were analyzed by direct infusion ESI(+)-MS, which provides characteristic fingerprints of the sample composition. 3-Deoxyanthocyanidins are important substances in A. chica, their ions were used as markers in the PLS-DA data treatment. PLS-DA was able to differentiate the three varieties. ESI(+)-MS fingerprinting works as a simple and fast method to differentiate varieties of A. chica.

Nonculture-based identification of bacteria in milk by protein fingerprinting

Traditional methods for bacterial identification include Gram staining, culturing, and biochemical assays for phenotypic characterization of the causative organism. These methods can be time-consuming because they require in vitro cultivation of the microorganisms. Recently, however, it has become possible to obtain chemical profiles for lipids, peptides, and proteins that are present in an intact organism, particularly now that new developments have been made for the efficient ionization of biomolecules. MS has therefore become the state-of-the-art technology for microorganism identification in microbiological clinical diagnosis. Here, we introduce an innovative sample preparation method for nonculture-based identification of bacteria in milk. The technique detects characteristic profiles of intact proteins (mostly ribosomal) with the recently introduced MALDI SepsityperTM Kit followed by MALDI-MS. In combination with a dedicated bioinformatics software tool for databank matching, the method allows for almost real-time and reliable genus and species identification. We demonstrate the sensitivity of this protocol by experimentally contaminating pasteurized and homogenized whole milk samples with bacterial loads of 10(3)-10(8) colony-forming units (cfu) of laboratory strains of Escherichia coli, Enterococcus faecalis, and Staphylococcus aureus. For milk samples contaminated with a lower bacterial load (104 cfu mL-1), bacterial identification could be performed after initial incubation at 37 degrees C for 4 h. The sensitivity of the method may be influenced by the bacterial species and count, and therefore, it must be optimized for the specific application. The proposed use of protein markers for nonculture-based bacterial identification allows for high-throughput detection of pathogens present in milk samples. This method could therefore be useful in the veterinary practice and in the dairy industry, such as for the diagnosis of subclinical mastitis and for the sanitary monitoring of raw and processed milk products.