The Impact of Nutritional Supplementation on Sweat Metabolomic Content: A Proof-of-Concept Study.

Sweat is emerging as a prominent biosource for real-time human performance monitoring applications. Although promising, sources of variability must be identified to truly utilize sweat for biomarker applications. In this proof-of-concept study, a targeted metabolomics method was applied to sweat collected from the forearms of participants in a 12-week exercise program who ingested either low or high nutritional supplementation twice daily. The data establish the use of dried powder mass as a method for metabolomic data normalization from sweat samples. Additionally, the results support the hypothesis that ingestion of regular nutritional supplementation semi-quantitatively impact the sweat metabolome. For example, a receiver operating characteristic (ROC) curve of relative normalized metabolite quantities show an area under the curve of 0.82 suggesting the sweat metabolome can moderately predict if an individual is taking nutritional supplementation. Finally, a significant correlation between physical performance and the sweat metabolome are established. For instance, the data illustrate that by utilizing multiple linear regression modeling approaches, sweat metabolite quantities can predict VO2 max (p = 0.0346), peak lower body Windage (p = 0.0112), and abdominal circumference (p = 0.0425). The results illustrate the need to account for dietary nutrition in biomarker discovery applications involving sweat as a biosource.

Rate normalization for sweat metabolomics biomarker discovery.

As the demand for real-time exercise performance feedback increases, excreted sweat has become a biosource of interest for continuous human performance assessment. For sweat to truly fulfill this requirement, analyte concentrations must be normalized to adequately assess day-to-day differences within and among individuals. In this manuscript, data are presented highlighting the use of accurate localized sweat rate as a means for ion and global metabolomic data normalization. The results illustrate large sweat rate variability among individuals over the course of two distinct exercises protocols. Furthermore, the data show sweat rate is not symmetrical at similar locations among right and left forearms of individuals (p = 0.0007). Sweat ion conductivity analysis suggest overall sweat rate normalization reduces variability collectively among ion values and participants with principal component analysis showing 77.8% of variation in the data set attributable to sweat rate normalization. Global metabolomic analysis of sweat illustrated overall rate normalization increases the variability among test subjects with 72.7% of the variation explained by sweat rate normalization. Finally, overall rate normalized metabolomic features of sweat significantly correlated (ρ ≥ 0.7, ρ ≤ -0.7) with measured performance metrics of the individual, establishing the potential for sweat to be used as a biosource for performance monitoring. Collectively, these data illustrate the importance of accurate localized sweat rate determination, for analyte data normalization, in support for the use of sweat in biomarker discovery efforts to predict human performance.

Analysis of Lipids in Single Cells and Organelles Using Nanomanipulation-Coupled Mass Spectrometry.

The ability to discriminately analyze the chemical constituents of single cells and organelles is highly sought after and necessary to establish true biomarkers. Some major challenges of individual cell analysis include requirement and expenditure of a large sample of cells as well as extensive extraction and separation techniques. Here, we describe methods to perform individual cell and organelle extractions of both tissues and cells in vitro using nanomanipulation coupled to mass spectrometry. Lipid profiles display heterogeneity from extracted adipocytes and lipid droplets, demonstrating the necessity for single cell analysis. The application of these techniques can be applied to other cell and organelle types for selective and thorough monitoring of disease progression and biomarker discovery.

Metabolomic stability of exercise-induced sweat.

Due to increased interest in the use of excreted sweat for biomarker discovery, data must be generated supporting sample collection and handling methods to allow for controlled, large-scale biomarker discovery studies to be performed. In this manuscript, twelve amino acids were quantitated from exercise-induced excreted sweat held at room temperature or a simulated body temperature of 37 °C for up to 90 min. The data illustrate a large dynamic range exists among amino acids in sweat. Additionally, the amino acid quantities vary across individuals and among the same individual under different storage conditions, with alanine, arginine, and threonine showing a significant statistical difference between sampling events (p < 0.05). Furthermore, the results establish amino acids are relatively invariant, at both storage temperatures tested, for up to 90 min illustrated by <10% (15/156) of the amino acids measurements demonstrating change greater than 10% from the time zero value. An untargeted metabolomics approach was also applied to the data set to evaluate global changes to the metabolome. The results show more than 88% of all data points fall within the established limits, regardless of temperature condition and ionization mode. Collectively, this study demonstrates that sweat is largely invariant at two distinct temperatures for up to 90 min. These results establish sweat collection and sample handling is possible for up to 90 min with minimal changes in metabolite abundances.

Nanomanipulation-Coupled Matrix-Assisted Laser Desorption/ Ionization-Direct Organelle Mass Spectrometry: A Technique for the Detailed Analysis of Single Organelles.

We describe a novel technique combining precise organelle microextraction with deposition and matrix-assisted laser desorption/ionization (MALDI) for a rapid, minimally invasive mass spectrometry (MS) analysis of single organelles from living cells. A dual-positioner nanomanipulator workstation was utilized for both extraction of organelle content and precise co-deposition of analyte and matrix solution for MALDI-direct organelle mass spectrometry (DOMS) analysis. Here, the triacylglycerol (TAG) profiles of single lipid droplets from 3T3-L1 adipocytes were acquired and results validated with nanoelectrospray ionization (NSI) MS. The results demonstrate the utility of the MALDI-DOMS technique as it enabled longer mass analysis time, higher ionization efficiency, MS imaging of the co-deposited spot, and subsequent MS/MS capabilities of localized lipid content in comparison to NSI-DOMS. This method provides selective organellar resolution, which complements current biochemical analyses and prompts for subsequent subcellular studies to be performed where limited samples and analyte volume are of concern. Graphical Abstract ᅟ.