Fatiguing freestyle swimming modifies miRNA profiles of circulating extracellular vesicles in athletes

HR, RPE results

The mean HR level of the subjects after a full 1500-m freestyle exercise was > 185 bpm. The RPE value was higher than 19, an extremely high level and a significant increase compared to the baseline (RPE 9).

Bla, CK, 5-HT test results

The subjects’ Bla significantly increased immediately after the full 1500-m freestyle exercise (p < 0.01) (Fig. 1A), reaching 11.2 mmol/L. The CK of the subjects increased significantly after the 1500-m exercise (p < 0.01) (Fig. 1B), reaching a maximum of 340 U/L.

Fig. 1figure 1

Changes in subjects' blood indicators; *p < 0.05, **p < 0.01 compared with baseline. CK creatine kinase; Bla blood lactic acid; 5-HT serotonin. A Bla significantly increased, p < 0.01. B The CK of the subjects increased significantly, p < 0.01. C The levels of 5-HT significantly increased, p < 0.05

As a central neurotransmitter in the brain, the concentration of 5-HT, one of the criteria for central nervous system fatigue, significantly increased after exercise (p < 0.05) (Fig. 1C).

Anaerobic test results

After the full 1500-m freestyle exercise, no significant changes were observed in the subjects' PP (w) and PP (w/kg) (Fig. 2A, B). In sharp contrast, a series of anaerobic exercise metrics significantly increased at the p < 0.05 level, including subjects' PD (w), PD (w/kg), FIpp, and PD (%) (Fig. 2C–F).

Fig. 2figure 2

Changes in the subjects’ anaerobic capacity indicators as compared with baseline. PP (W), maximum power; PP (W/kg), relative maximum power; PD (W), power decline; PD (W/kg), relative power decline; FIpp, power decline rate; PD (%), fatigue percentage. A The subjects' PP (w) did not change significantly. B The subjects' PP (w/kg) did not change significantly. C The subjects' PD (w) significantly increased at p < 0.05. D The subjects' PD (w/kg) significantly increased at p < 0.05. E The subjects' FIpp significantly increased at p < 0.05. F The subjects' PD (%) significantly increased at p < 0.05

Changes of plasma EV-miRNAs in 1500-m freestyle swimmers under exercise fatigueIdentification results of EVs

To identify the EVs extracted from plasma samples, the morphology, particle size and distribution, and protein markers of plasma extracts were detected. Through TEM, the morphology of the extracted EVs in plasma was observed to be elliptical, and the diameter of the particles was ~ 100–200 nm (Fig. 3A). Through NTA analysis, we observed that the diameter of EV particles ranged from 40 to 200 nm, among which the particles with a diameter of 145 nm accounted for the highest proportion (Fig. 3B). The expression of EV marker proteins CD63 and ALIX were detected by WB (Fig. 3C).

Fig. 3figure 3

EVs in plasma identification results. A Image of EVs observed by TEM electron microscope. The diameter is about 200 nm. B NTA analysis. The abscissa is the diameter of EVs, the ordinate is their number and concentration. C Detection of EVs by Western blots body marker proteins CD63 and ALIX

Measurement of total RNA concentration

The concentration, total amount, and volume of total RNA were > 0.3 ng/μL, >13 ng, and 38 μL, respectively, as detected through Agilent 2100. As listed in Table 2, the quality of total miRNA extracted from the subjects' EVs in plasma met the test requirements, in that the concentration, volume, and purity of miRNAs could be satisfactorily used for database construction and subsequent trials.

Table 2 Total RNA concentration of EVs in plasmaQuality control of miRNAs’ detection

The miRNAs’ data obtained by preliminary filtering of the original miRNAs were further filtered. The number of bases with a quality value < 20 in the filtered data exceeded 1 read, and high-quality reads were obtained. After filtering out reads containing polyA and greater than 70% of the base reads, the small RNA clean tags sequence that could be used for subsequent analysis was finally acquired (Fig. 4).

Fig. 4figure 4

Quality control of the sample

The differential expressions of miRNAs in EVs

By integrating high-throughput sequencing with the three miRNAs’ target gene prediction databases (PITA, Targetscan, and miRand), subjects’ plasma EV-miRNAs expressions were analyzed in detail before and after exercise. In plasma, EV-miRNAs with a value of p < 0.05 and │log2(fold-change)│> 1 were considered to be differentially expressed. In total, 70 EV-miRNAs were found with significantly differential expression, among which 45 and 25 miRNAs were up-regulated and down-regulated, respectively (see Table 3). Three miRNAs were screened out due to their up-regulated expression after exercise and fold change being > 11, which included miR-144-3p, miR-145-3p, and miR-509-5p. Two miRNAs (miR-891b and miR-890) were filtered out due to their down-regulated expression and their fold change being > 9. Subsequently, the target genes regulated by the aforementioned five miRNAs were predicted prior to functional enrichment analysis.

Table 3 Differentially expressed profiles of EV-miRNAsFunctional enrichment analyses of target genes regulated by EV-miRNAs

The five target genes of miR-144-3p, miR-145-3p, miR-509-5p, miR-891b and miR-890 were predicted to be differentially expressed through three databases of PITA, Targetscan, and miRand. Using GO and KEGG databases the functional annotation was analyzed to find the intersection relationship.

Figure 5 shows the statistical results of the comparison and classification of the target genes of differentially expressed EV-miRNAs in plasma through the GO database. In GO enrichment, three aspects are involved: biological process, cell composition, and molecular function, and each aspect is composed of eight items. Target genes are involved in cell metabolism, biological regulation, and signal transmission. They are mainly distributed in cell parts, membrane-enclosed cavities, and extracellular areas, and become enriched in molecular functions such as signal transmission, protein binding, and structural molecular activity.

Fig. 5figure 5

Differentially expressed EV-miRNAs GO function classification map

The abscissa is the GO annotation, and the ordinate represents the number of genes. Green represents the biological process, red the cell composition, and blue the molecular function.

By screening the significantly enriched KEGG signaling pathways, the target genes regulated by the EV-miRNAs become mainly enriched in metabolic, calcium signaling, GnRH signaling and VEGF signaling pathways; long-term enhancement mechanism (long-term potentiation, or LTP); dopaminergic and cholinergic synapse; Alzheimer’s disease (AD); and glutathione, glycerophospholipid, and arachidonic acid metabolism, among others (Fig. 6). Consequently, it can be posited that EV-miRNAs are related to the enrichment of multiple signaling pathways, including those related to energy metabolism, skeletal muscle, central nervous system, immunity, and tumors. The database test shows that the metabolic pathways are the most significant and are closely related to EV-miRNAs target genes.

Fig. 6figure 6

Differentially expressed EV-miRNAs target gene KEGG signaling pathway enrichment map

The color depth (Q value) indicates the enrichment degree of differentially expressed EV-miRNAs target genes in the signal pathway. The size of the circle (Gene number) denotes the number of genes with the differentially expressed EV-miRNAs target gene located under the signal pathway.

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