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Sweat contains biomarkers for real-time non-invasive health monitoring, but only a few relevant analytes are currently used in clinical practice. In the present study, we investigated whether sweat-derived extracellular vesicles (EVs) can be used as a source of potential protein biomarkers of human and bacterial origin. Methods: By using ExoView platform, electron microscopy, nanoparticle tracking analysis and Western blotting we characterized EVs in the sweat of eight volunteers performing rigorous exercise. We compared the presence of EV markers as well as general protein composition of total sweat, EV-enriched sweat and sweat samples collected in alginate skin patches. Results: We identified 1209 unique human proteins in EV-enriched sweat, of which approximately 20% were present in every individual sample investigated. Sweat derived EVs shared 846 human proteins (70%) with total sweat, while 368 proteins (30%) were captured by medical grade alginate skin patch and such EVs contained the typical exosome marker CD63. The majority of identified proteins are known to be carried by EVs found in other biofluids, mostly urine. Besides human proteins, EV-enriched sweat samples contained 1594 proteins of bacterial origin. Bacterial protein profiles in EV-enriched sweat were characterized by high interindividual variability, that reflected differences in total sweat composition. Alginate-based sweat patch accumulated only 5% proteins of bacterial origin. Conclusion: We showed that sweat-derived EVs provide a rich source of potential biomarkers of human and bacterial origin. Use of commercially available alginate skin patches selectively enrich for human derived material with very little microbial material collected., Competing Interests: Competing Interests: The authors have declared that no competing interest exists., (© The author(s).)

Background: The human sweat is a mixture of secretions from three types of glands: eccrine, apocrine, and sebaceous. Eccrine glands open directly on the skin surface and produce high amounts of water-based fluid in response to heat, emotion, and physical activity, whereas the other glands produce oily fluids and waxy sebum. While most body fluids have been shown to contain nucleic acids, both as ribonucleoprotein complexes and associated with extracellular vesicles (EVs), these have not been investigated in sweat. In this study we aimed to explore and characterize the nucleic acids associated with sweat particles., Results: We used next generation sequencing (NGS) to characterize DNA and RNA in pooled and individual samples of EV-enriched sweat collected from volunteers performing rigorous exercise. In all sequenced samples, we identified DNA originating from all human chromosomes, but only the mitochondrial chromosome was highly represented with 100% coverage. Most of the DNA mapped to unannotated regions of the human genome with some regions highly represented in all samples. Approximately 5 % of the reads were found to map to other genomes: including bacteria (83%), archaea (3%), and virus (13%), identified bacteria species were consistent with those commonly colonizing the human upper body and arm skin. Small RNA-seq from EV-enriched pooled sweat RNA resulted in 74% of the trimmed reads mapped to the human genome, with 29% corresponding to unannotated regions. Over 70% of the RNA reads mapping to an annotated region were tRNA, while misc. RNA (18,5%), protein coding RNA (5%) and miRNA (1,85%) were much less represented. RNA-seq from individually processed EV-enriched sweat collection generally resulted in fewer percentage of reads mapping to the human genome (7-45%), with 50-60% of those reads mapping to unannotated region of the genome and 30-55% being tRNAs, and lower percentage of reads being rRNA, LincRNA, misc. RNA, and protein coding RNA., Conclusions: Our data demonstrates that sweat, as all other body fluids, contains a wealth of nucleic acids, including DNA and RNA of human and microbial origin, opening a possibility to investigate sweat as a source for biomarkers for specific health parameters.