Non-invasive and accurate access of biomarkers remains a holy grail of the biomedical community. Human eccrine sweat is a surprisingly biomarker-rich fluid which is gaining increasing attention. This is especially true in applications of continuous bio-monitoring where other biofluids prove more challenging, if not impossible. However, much confusion on the topic exists as the microfluidics of the eccrine sweat gland has never been comprehensively presented and models of biomarker partitioning into sweat are either underdeveloped and/or highly scattered across literature. Reported here are microfluidic models for eccrine sweat generation and flow which are coupled with review of blood-to-sweat biomarker partition pathways, therefore providing insights such as how biomarker concentration changes with sweat flow rate. Additionally, it is shown that both flow rate and biomarker diffusion determine the effective sampling rate of biomarkers at the skin surface (chronological resolution). The discussion covers a broad class of biomarkers including ions (Na(+), Cl(-), K(+), NH4 (+)), small molecules (ethanol, cortisol, urea, and lactate), and even peptides or small proteins (neuropeptides and cytokines). The models are not meant to be exhaustive for all biomarkers, yet collectively serve as a foundational guide for further development of sweat-based diagnostics and for those beginning exploration of new biomarker opportunities in sweat.
SummaryThe addition of 1-20% (v/v) of methanol or acetonitrile as organic modifier to the mobile phase in a micellar electrokinetic capillary chromatographic (MECC) system, containing sodium dodecyl sulfate and a buffer, is shown to extend the elution range and thus increase the peak capacity of a given system. Although thenet changein theelution rangeparameter, tO/tmc,is essentially the same for both modifiers, the acetonitrile-modified system exhibits much faster elution times for the polar and non-polar test solutes employed in this study. Retention, as measured by thecapacity factor, is generally decreased with the increaseof anorganic modifier, just as in conventional reversedphase chromatography. However, changes in selectivity as a function of the added modifiers are noted among polar and nonpolar solutes as well. The efficiency of these MECC systems is increased with the addition of either organic modifier.
BackgroundEven though human sweat is odorless, bacterial growth and decomposition of specific odor precursors in it is believed to give rise to body odor in humans. While mechanisms of odor generation have been widely studied in adults, little is known for teenagers and pre-pubescent children who have distinct sweat composition from immature apocrine and sebaceous glands, but are arguably more susceptible to the social and psychological impact of malodor.ResultsWe integrated information from whole microbiome analysis of multiple skin sites (underarm, neck, and head) and multiple time points (1 h and 8 h after bath), analyzing 180 samples in total to perform the largest metagenome-wide association study to date on malodor. Significant positive correlations were observed between odor intensity and the relative abundance of Staphylococcus hominis, Staphylococcus epidermidis, and Cutibacterium avidum, as well as negative correlation with Acinetobacter schindleri and Cutibacterium species. Metabolic pathway analysis highlighted the association of isovaleric and acetic acid production (sour odor) from enriched S. epidermidis (teen underarm) and S. hominis (child neck) enzymes and sulfur production from Staphylococcus species (teen underarm) with odor intensity, in good agreement with observed odor characteristics in pre-pubescent children and teenagers. Experiments with cultures on human and artificial sweat confirmed the ability of S. hominis and S. epidermidis to independently produce malodor with distinct odor characteristics.ConclusionsThese results showcase the power of skin metagenomics to study host-microbial co-metabolic interactions, identifying distinct pathways for odor generation from sweat in pre-pubescent children and teenagers and highlighting key enzymatic targets for intervention.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0588-z) contains supplementary material, which is available to authorized users.
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