Rapid characterization of lipids by MALDI MS. Part 2: Artifacts, ion suppression, and TLC MALDI imaging

Matrix-assisted ionization Fourier transform mass spectrometry for the analysis of lipids

RATIONALE

Assessing the utility of vacuum matrix-assisted ionization (MAI) for the direct and rapid analysis of lipids in complex samples with emphasis on bacterial taxonomy.

METHODS

Matrix-assisted ionization Fourier transform mass spectrometry (MAI-FTMS) was used to characterize polar and non-polar lipids in mixtures.

RESULTS

For non-polar lipid triacylglycerols (TAGs), MAI-FTMS produced lipid-specific ions for eight different edible oils and allowed these oils to be identified based on their MAI-FTMS profiles. For polar lipids from bacteria, MAI-FTMS of crude lipid extracts allowed taxonomic identification of eight blind-coded samples based on taxonomy-specific phospholipid profiles. MAI produced results comparable and complementary to benchmark MALDI and ESI methods currently used for characterization of polar and non-polar lipids in the same mixtures.

CONCLUSIONS

The newly developed MAI technique is a rapid, simple and complementary method for the characterization of polar and non-polar lipids in complex mixtures.

DAPNe with micro-capillary separatory chemistry-coupled to MALDI-MS for the analysis of polar and non-polar lipid metabolism in one cell

The cellular metabolome is considered to be a representation of cellular phenotype and cellular response to changes to internal or external events. Methods to expand the coverage of the expansive physiochemical properties that makeup the metabolome currently utilize multi-step extractions and chromatographic separations prior to chemical detection, leading to lengthy analysis times. In this study, a single-step procedure for the extraction and separation of a sample using a micro-capillary as a separatory funnel to achieve analyte partitioning within an organic/aqueous immiscible solvent system is described. The separated analytes are then spotted for MALDI-MS imaging and distribution ratios are calculated. Initially, the method is applied to standard mixtures for proof of partitioning. The extraction of an individual cell is non-reproducible; therefore, a broad chemical analysis of metabolites is necessary and will be illustrated with the one-cell analysis of a single Snu-5 gastric cancer cell taken from a cellular suspension. The method presented here shows a broad partitioning dynamic range as a single-step method for lipid analysis demonstrating a decrease in ion suppression often present in MALDI analysis of lipids. Graphical Abstract ᅟ.

Correlated imaging with C60-SIMS and confocal Raman microscopy: Visualization of cell-scale molecular distributions in bacterial biofilms

Secondary ion mass spectrometry (SIMS) and confocal Raman microscopy (CRM) are combined to analyze the chemical composition of cultured Pseudomonas aeruginosa biofilms, providing complementary chemical information for multiple analytes within the sample. Precise spatial correlation between SIMS and CRM images is achieved by applying a chemical microdroplet array to the sample surface which is used to navigate the sample, relocate regions of interest, and align image data. CRM is then employed to nondestructively detect broad molecular constituent classes-including proteins, carbohydrates, and, for the first time, quinolone signaling molecules-in Pseudomonas-derived biofilms. Subsequent SIMS imaging at the same location detects quinolone distributions in excellent agreement with the CRM, discerns multiple quinolone species which differ slightly in mass, resolves subtle differences in their distributions, and resolves ambiguous compound assignments from CRM by determining specific molecular identities via in situ tandem MS.

Correlated imaging--a grand challenge in chemical analysis

Correlated chemical imaging is an emerging strategy for acquisition of images by combining information from multiplexed measurement platforms to track, visualize, and interpret in situ changes in the structure, organization, and activities of interesting chemical systems, frequently spanning multiple decades in space and time. Acquiring and correlating information from complementary imaging experiments has the potential to expose complex chemical behavior in ways that are simply not available from single methods applied in isolation, thereby greatly amplifying the information gathering power of imaging experiments. However, in order to correlate image information across platforms, a number of issues must be addressed. First, signals are obtained from disparate experiments with fundamentally different figures of merit, including pixel size, spatial resolution, dynamic range, and acquisition rates. In addition, images are often acquired on different instruments in different locations, so the sample must be registered spatially so that the same area of the sample landscape is addressed. The signals acquired must be correlated in both spatial and temporal domains, and the resulting information has to be presented in a way that is readily understood. These requirements pose special challenges for image cross-correlation that go well beyond those posed in single technique imaging approaches. The special opportunities and challenges that attend correlated imaging are explored by specific reference to correlated mass spectrometric and Raman imaging, a topic of substantial and growing interest.