Detection of carbohydrates and steroids by cation-enhanced nanostructure-initiator mass spectrometry (NIMS) for biofluid analysis and tissue imaging.

Nanostructure-initiator mass spectrometry (NIMS) is a highly sensitive, matrix-free technique that is well suited for biofluid analysis and imaging of biological tissues. Here we provide a new technical variation of NIMS to analyze carbohydrates and steroids, molecules that are challenging to detect with traditional mass spectrometric approaches. Analysis of carbohydrates and steroids was accomplished by spray depositing NaCl or AgNO(3) on the NIMS porous silicon surface to provide a uniform environment rich with cationization agents prior to desorption of the fluorinated polymer initiator. Laser desorption/ionization of the ion-coated NIMS surface allowed for Na(+) cationization of carbohydrates and Ag(+) cationization of steroids. The reliability of the approach is quantitatively demonstrated with a calibration curve over the physiological range of glucose and cholesterol concentrations in human serum (1-200 microM). Additionally, we illustrate the sensitivity of the method by showing its ability to detect carbohydrates and steroids down to the 800-amol and 100-fmol levels, respectively. The technique developed is well suited for tissue imaging of biologically significant metabolites such as sucrose and cholesterol. To highlight its applicability, we used cation-enhanced NIMS to image the distribution of sucrose in a Gerbera jamesonii flower stem and the distribution of cholesterol in a mouse brain. The flower stem and brain sections were placed directly on the ion-coated NIMS surface without further preparation and analyzed directly. The overall results reported underscore the potential of NIMS to analyze and image chemically diverse compounds that have been traditionally challenging to observe with mass spectrometry-based techniques.

Selective metabolite and peptide capture/mass detection using fluorous affinity tags.

A new and general methodology is described for the targeted enrichment and subsequent direct mass spectrometric characterization of sample subsets bearing various chemical functionalities from highly complex mixtures of biological origin. Specifically, sample components containing a chemical moiety of interest are first selectively labeled with perfluoroalkyl groups, and the entire sample is then applied to a perfluoroalkyl-silylated porous silicon (pSi) surface. Due to the unique hydrophobic and lipophobic nature of the perfluorinated tags, unlabeled sample components are readily removed using simple surface washes, and the enriched sample fraction can then directly be analyzed by desorption/ionization on silicon mass spectrometry (DIOS-MS). Importantly, this fluorous-based enrichment methodology provides a single platform that is equally applicable to both peptide as well as small molecule focused applications. The utility of this technique is demonstrated by the enrichment and mass spectrometric analysis of both various peptide subsets from protein digests as well as amino acids from serum.

Mass spectrometry reveals specific and global molecular transformations during viral infection.

Mass spectrometry analysis was used to target three different aspects of the viral infection process: the expression kinetics of viral proteins, changes in the expression levels of cellular proteins, and the changes in cellular metabolites in response to viral infection. The combination of these methods represents a new, more comprehensive approach to the study of viral infection revealing the complexity of these events within the infected cell. The proteins associated with measles virus (MV) infection of human HeLa cells were measured using a label-free approach. On the other hand, the regulation of cellular and Flock House Virus (FHV) proteins in response to FHV infection of Drosophila cells was monitored using stable isotope labeling. Three complementary techniques were used to monitor changes in viral protein expression in the cell and host protein expression. A total of 1500 host proteins was identified and quantified, of which over 200 proteins were either up- or down-regulated in response to viral infection, such as the up-regulation of the Drosophila apoptotic croquemort protein, and the down-regulation of proteins that inhibited cell death. These analyses also demonstrated the up-regulation of viral proteins functioning in replication, inhibition of RNA interference, viral assembly, and RNA encapsidation. Over 1000 unique metabolites were also observed with significant changes in over 30, such as the down-regulated cellular phospholipids possibly reflecting the initial events in cell death and viral release. Overall, the cellular transformation that occurs upon viral infection is a process involving hundreds of proteins and metabolites, many of which are structurally and functionally uncharacterized.

Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry.

The aim of metabolite profiling is to monitor all metabolites within a biological sample for applications in basic biochemical research as well as pharmacokinetic studies and biomarker discovery. Here, novel data analysis software, XCMS, was used to monitor all metabolite features detected from an array of serum extraction methods, with application to metabolite profiling using electrospray liquid chromatography/mass spectrometry (ESI-LC/MS). The XCMS software enabled the comparison of methods with regard to reproducibility, the number and type of metabolite features detected, and the similarity of these features between different extraction methods. Extraction efficiency with regard to metabolite feature hydrophobicity was examined through the generation of unique feature density distribution plots, displaying feature distribution along chromatographic time. Hierarchical clustering was performed to highlight similarities in the metabolite features observed between the extraction methods. Protein extraction efficiency was determined using the Bradford assay, and the residual proteins were identified using nano-LC/MS/MS. Additionally, the identification of four of the most intensely ionized serum metabolites using FTMS and tandem mass spectrometry was reported. The extraction methods, ranging from organic solvents and acids to heat denaturation, varied widely in both protein removal efficiency and the number of mass spectral features detected. Methanol protein precipitation followed by centrifugation was found to be the most effective, straightforward, and reproducible approach, resulting in serum extracts containing over 2000 detected metabolite features and less than 2% residual protein. Interestingly, the combination of all approaches produced over 10,000 unique metabolite features, a number that is indicative of the complexity of the human metabolome and the potential of metabolomics in biomarker discovery.

Surfactant-enhanced desorption/ionization on silicon mass spectrometry.

Perfluorinated surfactants are demonstrated to dramatically enhance desorption/ionization on fluorinated silicon (DIOS) mass spectrometry. Perfluorooctanesulfonic acid improved the signal-to-noise ratio of tryptic digests and gave a 3-fold increase in the number of peptides identified. Similar results were also obtained using perfluoroundecanoic acid; yet among the seven different surfactants tested, controls such as nonfluorinated sodium dodecyl sulfate or fluorinated molecules with minimal surfactant activity did not enhance the signal. The same surfactants also enhanced the DIOS-MS signal of amino acids, carbohydrates, and other small organic compounds. The signal enhancement may be facilitated by the high surface activity of the perfluorinated surfactants on the fluorinated silicon surfaces allowing for a higher concentration of analyte to be absorbed.