Detection and Imaging of Exposure-Related Metabolites and Xenobiotics in Hard Tissues by Laser Sampling and Mass Spectrometry.

The utility of two novel laser-based methods, laser ablation electrospray ionization (LAESI) and laser desorption ionization (LDI) from silicon nanopost array (NAPA), is explored via local analysis and mass spectrometry imaging (MSI) of hard tissues (tooth and hair) for the detection and mapping of organic components. Complex mass spectra are recorded in local analysis mode from tooth dentin and scalp hair samples. Nicotine and its metabolites (cotinine, hydroxycotinine, norcotinine, and nicotine) are detected by LAESI-MS in the teeth of rats exposed to tobacco smoke. The intensities of the detected metabolite peaks are proportional to the degree of exposure. Incorporating ion mobility separation in the LAESI-MS analysis of scalp hair enables the detection of cotinine in smoker hair along with other common molecular species, including endogenous steroid hormones and some lipids. Single hair strands are imaged by MALDI-MSI and NAPA-LDI-MSI to explore longitudinal variations in the level of small molecules. Comparing spectra integrated from NAPA-LDI-MSI and MALDI-MSI images reveals that the two techniques provide complementary information. There were 105 and 82 sample-related peaks for MALDI and NAPA, respectively, with an overlap of only 16 peaks, indicating a high degree of complementarity. Enhanced molecular coverage and spatial resolution offered by LAESI-MS and NAPA-LDI-MSI can reveal the distributions of known and potential biomarkers in hard tissues, facilitating exposome research.

Nutrient supplementation-induced metabolic profile changes and early appearance of free N-glycans in nutrient deficient tomato plants revealed by mass spectrometry.

Inorganic fertilizers are routinely used in large scale crop production for the supplementation of nitrogen, phosphorus, and potassium in nutrient poor soil. To explore metabolic changes in tomato plants grown on humic sand under different nutritional conditions, matrix-assisted laser desorption ionization (MALDI) mass spectrometry was utilized for the analysis of xylem sap. Variations in the abundances of metabolites and oligosaccharides, including free N-glycans (FNGs), were determined. Statistical analysis of the sample-related peaks revealed significant differences in the abundance ratios of multiple metabolites, including oligosaccharides, between the control plants, grown with no fertilizers, and plants raised under "ideal" and "nitrogen deficient" nutritional conditions, i.e., under the three treatment types. Among the 36 spectral features tentatively identified as oligosaccharides, the potential molecular structures for 18 species were predicted based on their accurate masses and isotope distribution patterns. To find the spectral features that account for most of the differences between the spectra corresponding to the three different treatments, multivariate statistical analysis was carried out by orthogonal partial least squares-discriminant analysis (OPLS-DA). They included both FNGs and non-FNG compounds that can be considered as early indicators of nutrient deficiency. Our results reveal that the potential nutrient deficiency indicators can be expanded to other metabolites beyond FNGs. The m/z values for 20 spectral features with the highest variable influence on projection (VIP) scores were ranked in the order of their influence on the statistical model.

High-Throughput f-LAESI-IMS-MS for Mapping Biological Nitrogen Fixation One Cell at a Time.

For the characterization of the metabolic heterogeneity of cell populations, high-throughput single-cell analysis platforms are needed. In this study, we utilized mass spectrometry (MS) enhanced with ion mobility separation (IMS) and coupled with an automated sampling platform, fiber-based laser ablation electrospray ionization (f-LAESI), for in situ high-throughput single-cell metabolomics in soybean (Glycine max) root nodules. By fully automating the in situ sampling platform, an overall sampling rate of 804 cells/h was achieved for high numbers (>500) of tissue-embedded plant cells. This is an improvement by a factor of 13 compared to the previous f-LAESI-MS configuration. By introducing IMS, the molecular coverage improved, and structural isomers were separated on a millisecond time scale. The enhanced f-LAESI-IMS-MS platform produced 259 sample-related peaks/cell, almost twice as much as the 131 sample-related peaks/cell produced by f-LAESI-MS without IMS. Using the upgraded system, two types of metabolic heterogeneity characterization methods became possible. For unimodal metabolite abundance distributions, the metabolic noise reported on the metabolite level variations within the cell population. For bimodal distributions, the presence of metabolically distinct subpopulations was established. Discovering these latent cellular phenotypes could be linked to the presence of different cell states, e.g., proliferating bacteria in partially occupied plant cells and quiescent bacteroids in fully occupied cells in biological nitrogen fixation, or spatial heterogeneity due to altered local environments.

Remote ablation chamber for high efficiency particle transfer in laser ablation electrospray ionization mass spectrometry.

Laser ablation electrospray ionization (LAESI) driven by mid-infrared laser pulses allows the direct analysis of biological tissues with minimal sample preparation. Dedicated remote ablation chambers have been developed to eliminate the need for close proximity between the sample and the mass spectrometer inlet. This also allows for the analysis of large or irregularly shaped objects, and incorporation of additional optics for microscopic imaging. Here we report on the characterization of a newly designed conical inner volume ablation chamber working in transmission geometry, where a reduced zone of stagnation was achieved by tapering the sample platform and the chamber outlet. As a result, the transmission efficiency of both large (>7.5 µm) and smaller particulates (<6.5 µm) has increased significantly. Improved analytical figures of merit, including 300 fmol limit of detection, and three orders of magnitude in dynamic range, were established. Particle residence time, measured by the FWHM of the analyte signal, was reduced from 2.0 s to 0.5 s enabling higher ablation rates and shorter analysis time. A total of six glucosinolates (sinigrin, gluconapin, progoitrin, glucoiberin, glucoraphanin, and glucohirsutin) were detected in plant samples with ion abundances higher by a factor of 2 to 8 for the redesigned ablation chamber.

Influence of the Structural Accuracy of Homology Models on Their Applicability to Docking-Based Virtual Screening: The ß2 Adrenergic Receptor as a Case Study.

How accurate do structures of the ß2 adrenergic receptor (ß2AR) need to be to effectively serve as platforms for docking-based virtual screening campaigns? To answer this research question, here, we targeted through controlled virtual screening experiments 23 homology models of the ß2AR endowed with different levels of structural accuracy. Subsequently, we studied the correlation between virtual screening performance and structural accuracy of the targeted models. Moreover, we studied the correlation between virtual screening performance and template/target receptor sequence identity. Our study demonstrates that docking-based virtual screening campaigns targeting homology models of the ß2AR, in the majority of the cases, yielded results that exceeded random expectations in terms of area under the receiver operating characteristic curve (ROC AUC). Moreover, with the most effective scoring method, over one-third and one-quarter of the models yielded results that exceeded random expectation also in terms of enrichment factors (EF1, EF5, and EF10) and BEDROC (α = 160.9), respectively. Not surprisingly, we found a detectable linear correlation between virtual screening performance and structural accuracy of the ligand-binding cavity. We also found a detectable linear correlation between virtual screening performance and structural accuracy of the second extracellular loop (EL2). Finally, our data indicate that, although there is no detectable linear correlation between virtual screening performance and template/ß2AR sequence identity, models built on the basis of templates that show high sequence identity with the ß2AR, especially within the ligand-biding cavity, performed consistently well. Conversely, models with lower sequence identity displayed performance levels that ranged from very good to random, with no apparent correlation with the sequence identity itself.