Literature DB >> 34103018

Characterization of nucleic acids from extracellular vesicle-enriched human sweat.

Geneviève Bart1, Daniel Fischer2, Anatoliy Samoylenko1, Artem Zhyvolozhnyi1, Pavlo Stehantsev1, Ilkka Miinalainen1, Mika Kaakinen1, Tuomas Nurmi1, Prateek Singh1,3, Susanna Kosamo1, Lauri Rannaste4, Sirja Viitala2, Jussi Hiltunen4, Seppo J Vainio5.   

Abstract

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.

Entities:  

Keywords:  Exercise; Extracellular vesicles (EV); Genomics; Metagenomics; Microbiome; Skin; Sweat; Transcriptomics

Mesh:

Substances:

Year:  2021        PMID: 34103018     DOI: 10.1186/s12864-021-07733-9

Source DB:  PubMed          Journal:  BMC Genomics        ISSN: 1471-2164            Impact factor:   3.969


  39 in total

1.  Correlation between sweat glucose and blood glucose in subjects with diabetes.

Authors:  James Moyer; Donald Wilson; Irina Finkelshtein; Bruce Wong; Russell Potts
Journal:  Diabetes Technol Ther       Date:  2012-02-29       Impact factor: 6.118

2.  Holocrine Secretion of Sebum Is a Unique DNase2-Dependent Mode of Programmed Cell Death.

Authors:  Heinz Fischer; Judith Fumicz; Heidemarie Rossiter; Markus Napirei; Maria Buchberger; Erwin Tschachler; Leopold Eckhart
Journal:  J Invest Dermatol       Date:  2016-10-19       Impact factor: 8.551

3.  Proteomic profiling of eccrine sweat reveals its potential as a diagnostic biofluid for active tuberculosis.

Authors:  Olanisun Olufemi Adewole; Greg Efosa Erhabor; Temitayo Oluwatoyin Adewole; Abiodun Oluwasesan Ojo; Harriet Oshokoya; Lisa M Wolfe; Jessica E Prenni
Journal:  Proteomics Clin Appl       Date:  2016-04-01       Impact factor: 3.494

Review 4.  The human skin microbiome.

Authors:  Allyson L Byrd; Yasmine Belkaid; Julia A Segre
Journal:  Nat Rev Microbiol       Date:  2018-01-15       Impact factor: 60.633

5.  Ratiometric Fluorescent Nanohybrid for Noninvasive and Visual Monitoring of Sweat Glucose.

Authors:  Yaoxuan Cui; Wei Duan; Yao Jin; Fangjie Wo; Fengna Xi; Jianmin Wu
Journal:  ACS Sens       Date:  2020-06-22       Impact factor: 7.711

6.  Hepatitis C virus replicates in sweat glands and is released into sweat in patients with chronic hepatitis C.

Authors:  Nuria Ortiz-Movilla; Pablo Lázaro; Elena Rodríguez-Iñigo; Javier Bartolomé; Isabel Longo; Manuel Lecona; Margarita Pardo; Vicente Carreño
Journal:  J Med Virol       Date:  2002-12       Impact factor: 2.327

7.  Proteomic analysis of eccrine sweat: implications for the discovery of schizophrenia biomarker proteins.

Authors:  Michelle M Raiszadeh; Mark M Ross; Paul S Russo; Mary Ann Schaepper; Weidong Zhou; Jianghong Deng; Daniel Ng; April Dickson; Cindy Dickson; Monica Strom; Carolina Osorio; Thomas Soeprono; Julia D Wulfkuhle; Emanuel F Petricoin; Lance A Liotta; Wolff M Kirsch
Journal:  J Proteome Res       Date:  2012-02-27       Impact factor: 4.466

8.  In vivo single human sweat gland activity monitoring using coherent anti-Stokes Raman scattering and two-photon excited autofluorescence microscopy.

Authors:  X Chen; P Gasecka; F Formanek; J-B Galey; H Rigneault
Journal:  Br J Dermatol       Date:  2016-01-09       Impact factor: 9.302

Review 9.  The lipid droplet: A conserved cellular organelle.

Authors:  Congyan Zhang; Pingsheng Liu
Journal:  Protein Cell       Date:  2017-09-14       Impact factor: 14.870

10.  Wearable/disposable sweat-based glucose monitoring device with multistage transdermal drug delivery module.

Authors:  Hyunjae Lee; Changyeong Song; Yong Seok Hong; Minsung Kim; Hye Rim Cho; Taegyu Kang; Kwangsoo Shin; Seung Hong Choi; Taeghwan Hyeon; Dae-Hyeong Kim
Journal:  Sci Adv       Date:  2017-03-08       Impact factor: 14.957

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  2 in total

Review 1.  The Clinical Significance of Transfer RNAs Present in Extracellular Vesicles.

Authors:  Daniel S K Liu; Qi Zhi Clayton Yang; Mohammad Asim; Jonathan Krell; Adam E Frampton
Journal:  Int J Mol Sci       Date:  2022-03-28       Impact factor: 5.923

Review 2.  Next-Generation Sequencing for Confronting Virus Pandemics.

Authors:  Josep Quer; Sergi Colomer-Castell; Carolina Campos; Cristina Andrés; Maria Piñana; Maria Francesca Cortese; Alejandra González-Sánchez; Damir Garcia-Cehic; Marta Ibáñez; Tomàs Pumarola; Francisco Rodríguez-Frías; Andrés Antón; David Tabernero
Journal:  Viruses       Date:  2022-03-14       Impact factor: 5.048

  2 in total

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