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

Abstract

Extracellular vesicles (EVs) are secreted by various tissues and cells under normal physiological or pathological conditions. Exercise-induced EVs may be involved in the adaptation of exercise-induced fatigue. The 1500-m freestyle is the longest pool-based swimming event in the Olympic Games, and there is a paucity of information regarding changes in the miRNA profiles of circulating EVs after a single session of fatiguing swimming. In this study, 13 male freestyle swimmers conducted a fatiguing 1500-m freestyle swimming session at the speed of their best previously recorded swimming performance. Fasting venous blood was collected before and after the swimming session for analysis. 70 miRNAs from the circulating EVs were found to be differentially expressed after the fatiguing 1500-m freestyle swimming session, among which 45 and 25 miRNAs were up-regulated and down-regulated, respectively. As for the target genes of five miRNAs (miR-144-3p, miR-145-3p, miR-509-5p, miR-891b, and miR-890) with the largest expression-fold variation, their functional enrichment analysis demonstrated that the target genes were involved in the regulation of long-term potentiation (LTP), vascular endothelial growth factor (VEGF), glutathione metabolism pathway, dopaminergic synapse, signal transmission, and other biological processes. In summary, these findings reveal that a single session of fatiguing swimming modifies the miRNAs profiles of the circulating EVs, especially miR-144-3p, miR-145-3p, miR-509-5p, miR-891b, and miR-890, which clarifies new mechanisms for the adaptation to a single session of fatiguing exercise from the perspective of EV-miRNAs.

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European Journal of Applied Physiology (2023) 123:2041–2051
https://doi.org/10.1007/s00421-023-05167-7
ORIGINAL ARTICLE
Fatiguing freestyle swimming modifies miRNA profiles ofcirculating
extracellular vesicles inathletes
ZhijieLai1,2· WentaoLin3· XuYan4,5,6· XiaobinChen3· GuoqinXu3
Received: 27 August 2022 / Accepted: 22 February 2023 / Published online: 12 May 2023
© The Author(s) 2023
Abstract
Extracellular vesicles (EVs) are secreted by various tissues and cells under normal physiological or pathological conditions.
Exercise-induced EVs may be involved in the adaptation of exercise-induced fatigue. The 1500-m freestyle is the longest
pool-based swimming event in the Olympic Games, and there is a paucity of information regarding changes in the miRNA
profiles of circulating EVs after a single session of fatiguing swimming. In this study, 13 male freestyle swimmers conducted
a fatiguing 1500-m freestyle swimming session at the speed of their best previously recorded swimming performance. Fasting
venous blood was collected before and after the swimming session for analysis. 70 miRNAs from the circulating EVs were
found to be differentially expressed after the fatiguing 1500-m freestyle swimming session, among which 45 and 25 miRNAs
were up-regulated and down-regulated, respectively. As for the target genes of five miRNAs (miR-144-3p, miR-145-3p, miR-
509-5p, miR-891b, and miR-890) with the largest expression-fold variation, their functional enrichment analysis demonstrated
that the target genes were involved in the regulation of long-term potentiation (LTP), vascular endothelial growth factor
(VEGF), glutathione metabolism pathway, dopaminergic synapse, signal transmission, and other biological processes. In
summary, these findings reveal that a single session of fatiguing swimming modifies the miRNAs profiles of the circulating
EVs, especially miR-144-3p, miR-145-3p, miR-509-5p, miR-891b, and miR-890, which clarifies new mechanisms for the
adaptation to a single session of fatiguing exercise from the perspective of EV-miRNAs.
Keywords 1500-m freestyle· Extracellular vesicles· miRNA profile· Exercise-induced fatigue· Acute exercise
Introduction
Extracellular vesicles (EVs), including in particular
exosomes and microvesicles, are widely present in various
humoral samples, such as blood, urine, saliva, etc. Vari-
ous tissues and cells in the body have the ability to secrete
EVs under normal physiological or pathological conditions.
Studies have found that EVs are rich in various communi-
cation substances, such as nucleic acids, proteins, mRNA,
and microRNAs (miRNAs). Among them, miRNAs play a
key role in the exercise-regulated skeletal muscle energy
metabolism (Zhang etal. 2018; Whitham etal. 2018; Hou
etal. 2019). In recent years, studies have confirmed that
acute exercise increases circulating EVs, and exercise inten-
sity influences the response of EVs to endurance exercise
(Amosse etal. 2018; Wilhelm etal. 2017). EVs can promote
the repair and regeneration of skeletal muscle, enhance the
growth of nerve cells, and inhibit the differentiation of neu-
rons and the expression of pro-inflammatory factors (Qin
and Dallas 2019).
Communicated by Michael I Lindinger.
* Guoqin Xu
xugq@gzsport.edu.cn
1 Graduate School, Guangzhou Sport University,
Guangzhou510500, China
2 College ofPhysical Education, Guangzhou College
ofCommerce, Guangzhou511363, China
3 College ofExercise andHealth, Guangzhou Sport University,
Guangzhou510500, China
4 Institute forHealth andSport, Victoria University,
Melbourne3011, Australia
5 Australia Institute forMusculoskeletal Sciences, Melbourne,
VIC, Australia
6 Department ofMedicine-Western Health, The University
ofMelbourne, Melbourne, VIC, Australia
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2042 European Journal of Applied Physiology (2023) 123:2041–2051
1 3
The 1500-m freestyle is the longest pool-based swimming
event in the Olympic Games. Some of the key aspects in the
1500-m freestyle performance include how to effectively
improve energy utilization during competition, and how to
delay the occurrence of exercise-induced fatigue. Exercise-
induced fatigue is a common physiological phenomenon in
which the body cannot continue to maintain a certain level
or a predetermined intensity during exercise, resulting in a
decline in exercise capacity (Russell etal. 2020; Kieran etal.
2018). The occurrence of exercise fatigue is often viewed as a
common and complex phenomenon caused by abnormal neu-
romuscular functions, hormone disorders, protein imbalance,
increased inflammation and oxidative stress, and overtrain-
ing (Chen etal. 2019; Arthur etal. 2017; Wu and Liu 2018).
The essence of these abnormalities results from the decrease
in synaptic excitability of the central nervous system (CNS)
and the energy metabolism of skeletal muscles, which leads to
disturbances in homeostasis and susceptibility to injury (Jian
etal. 2012).However, studies on the expression of circulat-
ing EV-miRNAs after fatiguing exercise and the changes in
plasma EV-miRNAs after 1500m all-out freestyle swimming
are still scarce (Lipinska etal. 2015).
EV-miRNAs may be involved in the adaptation to exer-
cise-induced fatigue. A recent study on rats suggested that the
expression of EVs carried by miR-1 increased after exercise,
while the expressions of miR-133a, miR-133b, miR-206,
miR-208a, and miR-499 increased immediately after, but
returned to the baseline level after 48h. The rats’ exosomes
level remained unchanged at 24h after 4weeks of swimming
training, but a significant increase was observed immediately
after exercise. However, the expression of exosomes miR-1,
miR-486, miR-208a, miR-3571, miR-122, miR-196b, miR-
3591, miR-184, and miR-760 recovered after 24h (Brisamar
etal. 2020).These results provide evidence for physiological
adaptations to physical activity in EV-miRNAs (Lovett etal.
2018; D’Souza etal. 2018). There is a relative paucity of stud-
ies specifically relating to the changes of EVs in plasma and
the biological characteristics of miRNAs in EVs under an exer-
cise-induced fatigue state. Therefore, the aim of the study was
to reveal the characteristics of the EV-miRNAs in the plasma
of swimmers in a state of exercise-induced fatigue, and pro-
vide a theoretical basis for finding new biomarkers of exercise
fatigue. We hypothesized that the amount of EV-miRNAs in
plasma would increase after a full 1500-m freestyle swimming
session, and the differential profiles of circulating EV-miRNAs
would be modified by the fatiguing freestyle swimming.
Materials andmethods
Subjects
Thirteen male freestyle swimmers were recruited from
Guangzhou Sport University. Inclusion criteria included:
(1) nondrinker and nonsmoker; (2) non-fatigue in the past
2days. Each subject was informed of the research proce-
dures and objectives verbally and in writing, and a written
informed consent form was signed by each participant.
The study was approved by Guangzhou Sports University
Ethics Committee (Approval No. 2020LCLL-006). The
physical characteristics of the participants are summarized
in Table1.
Experimental program
One week before the swimming session, a baseline Win-
gate anaerobic power test was conducted on a MONARK-
894E power bicycle (Sweden), consisting of 30s of fastest
possible pedaling at a power load of the athlete’s weight
(kg) × 0.075. The maximum power (PP) and the relative
maximum power (PP/kg) were recorded. Power decline
(PD), relative power decline (PD/kg), power decline rate
(FIpp), and fatigue percentage (PD%) were used to evalu-
ate the anaerobic capacity of subjects.
In the morning of the swimming session, fasting venous
blood samples were collected. After reporting a rating of
perceived exertion (RPE) value and obtaining heart rate
data with a heart rate monitor (POLAR RC3, Finland), all
subjects commenced a 1500-m freestyle swimming session
at the speed of their best previously recorded swimming
performance (Matthews etal. 2016). After the swimming
session, the RPE scale was recorded to monitor the degree
of physical fatigue (Borg 1982); venous blood samples
were collected again, then the second Wingate anaerobic
power test was conducted.
Sample collection andpretreatment
Within half an hour after the collection of venous blood
samples, serum components were separated by centrifuga-
tion at 1000g for 15min, and stored in a freezer at −80°C
before further analysis.
Table 1 Subject characteristics
(N = 13)
BMI body mass index; HR heart rate; Training years of swimming training
Age (y) Height (cm) Weight (kg) BMI (kg/m2) HR (bpm) Training (y)
19.15 ± 1.07 180.31 ± 5.04 76.15 ± 9.72 24.25 ± 2.92 58.00 ± 4.76 8.54 ± 1.27
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2043European Journal of Applied Physiology (2023) 123:2041–2051
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Biochemical index assay
Blood lactic acid (Bla) was measured with EFK semi-auto-
matic lactic acid analyzer (EFK, German). Creatine kinase
(CK) in serum was detected using a fully automatic bio-
chemical analyzer (Chemray-420, Rayto, China).
ELISA
Serum samples were taken out from the −80°C freezer,
thawed on ice and centrifuged at 4°C with 2000g for 5min.
The level of Serotonin (5-HT) in serum was assayed by
ELISA (ABN-KA1894 Serotonin ELISA Kit) using a Mul-
tiskan Spectrum (Thermo Scientific, USA). Samples were
analyzed in duplicates.
EVs' isolation
Umibio Extracellular vesicles extraction kits (Umibio,
China) were used to isolate the EVs from plasma. 3mL of
pre-chilled PBS and 1mL of Blood Pure Exo Solution were
added to the stored supernatant. The mixture was vortexed
for 1min, incubated at 4°C for 2h, and centrifuged at 4°C
for 60min at 10,000g. The supernatant was discarded, while
the pellet rich in EV particles was resuspended with 0.5mL
of PBS. After it dissolved, the resuspension was transferred
to a new centrifuge tube.
Identification ofEVs withmicroscope
A transmission electron microscope (TEM) was used to
directly observe the characteristics and morphology of the
EVs for identification. After resuspending the extracted EVs
with 50–100μL of 2% paraformaldehyde, 50μL of the EVs
suspension were placed on copper mesh and allowed to stand
still at room temperature for 20min. 1% glutaraldehyde was
fixed for 5min; 4% uranyl acetate was used to negatively
stain for 5min, then the EVs pictures were photographed.
The EVs were tracked using Nanosight nanoparticle track-
ing analysis technology (NTA) and distinguished from other
particles, and finally the concentration and particle size dis-
tribution of EVs were detected.
Western blot
The isolated EVs were lysed with RIPA lysis buffer (Umibio,
China), and the protein concentration was determined
through BCA method. SDS-PAGE was performed on a 10%
polyacrylamide gel and transferred to a PVDF membrane.
This was sealed with 5% skimmed milk powder at room
temperature for 1h, incubated overnight at 4°C with a pri-
mary antibody (CD63, ALIX) solution, and followed by a
secondary antibody to block for 1h at room temperature.
Then, the protein bands were visualized using an enhanced
chemi-luminescence (ECL) reagent.
Total RNA extraction andconcentration assay
200μL of EVs sample were placed into a RNase-Free
centrifuge tube, mixed with an equal volume of 2 × dena-
turing solution, and placed on ice for 5min. 200μL of
phenol:chloroform solution were added into the tube, and
then vortexed for 30s, centrifuged at 10,000g for 5min at
4°C. The supernatant was transferred to a new centrifuge
tube, mixed with 1.25-fold volume of absolute ethanol, then
700μL of the solution was transferred to the spin column
and centrifuged at 10,000g for 30s at 4°C until it passed
through the column. 700μL of miRNA washing solution
1 was added, and centrifuged at 10,000g for 30s at 4°C
until it passed through the spin column. 500μL of washing
solution 2 was added, and centrifuged at 10,000g for 30s at
4°C until it passed through the spin column. The superna-
tant was discarded and the spin column was put back into
the collection tube. The resulting solution was centrifuged
at 10,000g for 1min at 4°C until it all passed through the
spin column. The adsorption column was put into a new col-
lection tube and 50μL of preheated washing solution were
added at 95°C. The precipitate (total RNA) was collected
by centrifugation for 30s, and the concentration of the total
RNA extracted from EVs was detected by means of an Agi-
lent 2100 Bioanalyzer System.
miRNA quality detection andlibrary construction
The 3′ and 5′ adapters were connected. 2μL of QIAseq
miRNA NGS RT Initiator were added for RNA reverse
transcription, and thoroughly mixed with QIAseq beads
and QIAseq miRNA NGS Bead Binding Buffer for mag-
netic beads (QMN Beads) preparation. cDNA synthesis
and purification were performed on ice, followed by library
amplification. PCR product fragments were screened, and
the concentration of the library was detected using Qubit
dsDNA HS assay. The Agilent 2100 Bioanalyzer High Sen-
sitivity DNA Assay was used to detect the fragment distri-
bution range of the library. The main peak of the library
was ~ 170–180bp. Finally, the high-throughput Illumina
2 × 150bp platform was used to detect the total miRNA
extracted from EVs (Dillies etal. 2013).
Differential expressions ofmiRNAs
Using the Expdiff method, the known miRNAs in EVs was
counted to determine whether there were significant differ-
ences in the expression levels between EVs, and the levels
of miRNAs co-expressed between samples were compared
using log2(fold-change) and scatter plots.
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2044 European Journal of Applied Physiology (2023) 123:2041–2051
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MiRNA pathway enrichment anddatum analysis
The R language package DEGseq was used to identify differ-
entially expressed genes. the R package based on differential
expression analysis of negative binomial distribution, and
the analysis of differentially expressed genes with biological
repetition. Three database tools: targetscan, miRanda, and
PITA were used to analyze the genetic sequence information
of the subjects with known miRNAs and newly predicted,
differentially expressed miRNAs (Wang etal. 2021; Zhang
2021). Finally, Gene Ontology (GO) and Kyoto Encyclo-
pedia of Genes and Genomes (KEGG) enrichment analysis
were performed on the set of miRNA target genes (Ash-
burner etal. 2000; Minoru etal. 2004). We used E-data soft-
ware to select the RT and ACC data generated by Stroop task
stimulus and imported it into WPS Excel 2019 to record.
Statistical analysis
All experimental data were recorded as mean ± standard
deviation (Mean ± SD), and SPSS 23.0 software was used
for statistical analysis. Each index before and after the exer-
cise was analyzed by paired sample T-test, and the statisti-
cal significance was expressed at the p < 0.05 or p < 0.01
level. Graphpad Prism 7.0 software was employed for image
drawing.
Results
HR, RPE results
The mean HR level of the subjects after a full 1500-m free-
style 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.
As a central neurotransmitter in the brain, the concentra-
tion of 5-HT, one of the criteria for central nervous sys-
tem 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).
Changes ofplasma EV‑miRNAs in1500‑m freestyle
swimmers underexercise fatigue
Identification results ofEVs
To identify the EVs extracted from plasma samples,
the morphology, particle size and distribution, and pro-
tein 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. 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
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2045European Journal of Applied Physiology (2023) 123:2041–2051
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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 concentra-
tion, volume, and purity of miRNAs could be satisfacto-
rily used for database construction and subsequent trials.
Fig. 2 Changes in the subjects’ anaerobic capacity indicators as com-
pared 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) signifi-
cantly 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
Fig. 3 EVs in plasma identifica-
tion 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
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2046 European Journal of Applied Physiology (2023) 123:2041–2051
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Quality 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).
The differential expressions ofmiRNAs inEVs
By integrating high-throughput sequencing with the three
miRNAs’ target gene prediction databases (PITA, Tar-
getscan, and miRand), subjects’ plasma EV-miRNAs
expressions were analyzed in detail before and after exer-
cise. In plasma, EV-miRNAs with a value of p < 0.05 and
│log2(fold-change)│> 1 were considered to be differen-
tially expressed. In total, 70 EV-miRNAs were found with
significantly differential expression, among which 45 and
25 miRNAs were up-regulated and down-regulated, respec-
tively (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 regu-
lated by the aforementioned five miRNAs were predicted
prior to functional enrichment analysis.
Functional 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 dif-
ferentially expressed through three databases of PITA, Tar-
getscan, 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 compari-
son 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 trans-
mission. They are mainly distributed in cell parts, mem-
brane-enclosed cavities, and extracellular areas, and become
enriched in molecular functions such as signal transmission,
protein binding, and structural molecular activity.
The abscissa is the GO annotation, and the ordinate rep-
resents the number of genes. Green represents the biological
process, red the cell composition, and blue the molecular
function.
By screening the significantly enriched KEGG signal-
ing pathways, the target genes regulated by the EV-miRNAs
Table 2 Total RNA concentration of EVs in plasma
Sample Volume
(μL) Agilent 2100 Results
Concentra-
tion (ng/
μL)
Volume
(μL) Total (ng)
I-3 98 0.347 38 13.186 Qualified
III-3 89 0.422 38 16.036 Qualified
I-6 90 0.546 38 20.748 Qualified
II-6 89 0.366 38 13.908 Qualified
I-7 89 0.546 38 20.748 Qualified
II-7 94 0.539 38 20.482 Qualified
I-11 86 0.464 38 17.632 Qualified
II-11 94 1.084 38 41.192 Qualified
I-13 92 0.352 38 13.376 Qualified
II-13 87 0.921 38 34.998 Qualified
Fig. 4 Quality control of the
sample
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2047European Journal of Applied Physiology (2023) 123:2041–2051
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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 sys-
tem, immunity, and tumors. The database test shows that the
metabolic pathways are the most significant and are closely
related to EV-miRNAs target genes.
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.
Discussion
Exercise fatigue is the main factor affecting athlete's training
and competition status. In this study, we used the evalua-
tion indicators of physiology and biochemistry to compre-
hensively observe the fatigue of freestyle athletes after a
1500-m freestyle swimming session. The profiles of plasma
EV-miRNAs under fatigue condition was obtained by high-
throughput detection technology, and the differentially
Table 3 Differentially expressed profiles of EV-miRNAs
Name Baseline Swim │log2FC│ Up/down
hsa-miR-144-3p 0.01 48.75166 12.25124 Up
hsa-miR-145-3p 0.01 37.47716 11.8718 Up
hsa-miR-509-5p 0.01 27.3532 11.41749 Up
hsa-miR-514b-5p 0.01 18.60436 10.86143 Up
hsa-miR-382-5p 0.01 10.52996 10.04028 Up
hsa-miR-495-3p 0.01 9.47388 9.887812 Up
hsa-miR-323a-3p 0.01 8.48148 9.728172 Up
hsa-miR-486-5p 22.5453 16608.1 9.524845 Up
hsa-miR-937-3p 0.01 5.83196 9.187837 Up
hsa-miR-432-5p 0.01 4.92952 8.945303 Up
hsa-miR-139-3p 0.01 3.56202 8.476552 Up
hsa-miR-451a 75.38478 23397.58 8.27787 Up
hsa-miR-329-3p 0.01 2.52236 7.97863 Up
hsa-miR-6509-5p 0.01 2.43168 7.92581 Up
hsa-miR-5699-5p 0.01 2.2845 7.835735 Up
hsa-miR-130b-3p 0.1075 19.8096 7.525719 Up
hsa-miR-145-5p 0.59878 66.87406 6.803277 Up
hsa-miR-143-3p 22.30074 2405.706 6.753225 Up
hsa-miR-214-3p 0.45108 23.01504 5.67305 Up
hsa-miR-142-5p 16.95878 477.292 4.814768 Up
hsa-miR-199a-3p 21.09196 534.1622 4.662513 Up
hsa-miR-199b-3p 21.09196 534.1622 4.662513 Up
hsa-miR-126-3p 36.12228 900.8692 4.640357 Up
hsa-miR-3679-5p 0.3065 6.39888 4.38386 Up
hsa-miR-1304-5p 0.45108 8.2739 4.197112 Up
hsa-miR-155-5p 21.87208 381.4561 4.124355 Up
hsa-miR-127-3p 0.50548 8.30728 4.03865 Up
hsa-miR-16-5p 729.2913 8404.447 3.526586 Up
hsa-miR-146a-5p 78.67734 676.7992 3.104708 Up
hsa-miR-223-3p 103.7061 858.5918 3.049472 Up
hsa-miR-503-5p 8.49 57.74774 2.765928 Up
hsa-miR-7-5p 85.14492 426.3318 2.323984 Up
hsa-miR-574-5p 87.84664 410.3965 2.223959 Up
hsa-miR-193a-5p 120.1112 489.9138 2.028157 Up
hsa-miR-1301-3p 34.95236 128.6871 1.880406 Up
hsa-miR-21-5p 20098.81 70769.04 1.816008 Up
hsa-miR-378a-3p 228.0371 648.5802 1.508016 Up
hsa-miR-320a-3p 3761.677 10578.35 1.491667 Up
hsa-let-7i-5p 2486.93 6794.987 1.450105 Up
hsa-let-7b-5p 21096.4 57066.43 1.435645 Up
hsa-miR-181b-5p 199.5891 539.3951 1.43431 Up
hsa-miR-132-3p 52.96718 141.6074 1.418726 Up
hsa-miR-15b-5p 246.7351 598.1228 1.277479 Up
hsa-miR-128-3p 312.1267 754.5679 1.273519 Up
hsa-miR-664a-5p 72.52922 151.0079 1.05799 Up
hsa-miR-891b 8.1684 0.01 9.730463 Down
hsa-miR-890 7.97184 0.01 9.67391 Down
hsa-miR-892b 8.49496 0.01 9.638769 Down
hsa-miR-92a-2-5p 6.33392 0.01 9.306955 Down
hsa-miR-548o-3p 6.26946 0.01 9.292197 Down
Table 3 (continued)
Name Baseline Swim │log2FC│ Up/down
hsa-miR-20a-3p 4.89706 0.01 8.935772 Down
hsa-miR-888-5p 171.1154 0.3672 8.864188 Down
hsa-miR-874-5p 4.03866 0.01 8.657733 Down
hsa-miR-3144-3p 2.3336 0.01 7.866413 Down
hsa-miR-891a-5p 464.5873 13.62056 5.092092 Down
hsa-miR-577 12.3276 0.4141 4.895769 Down
hsa-miR-892a 15.66568 0.55072 4.830145 Down
hsa-miR-497-5p 3.84982 0.1889 4.349096 Down
hsa-miR-187-3p 20.80978 1.65506 3.652306 Down
hsa-miR-582-5p 38.0094 4.47352 3.086874 Down
hsa-miR-653-3p 32.38488 4.47938 2.853949 Down
hsa-miR-590-3p 17.02644 2.61344 2.703755 Down
hsa-miR-187-5p 13.6263 2.1745 2.647638 Down
hsa-miR-628-5p 10.29026 2.69618 1.932291 Down
hsa-miR-1296-5p 12.02364 4.1779 1.525024 Down
hsa-miR-30b-5p 10245.37 3857.633 1.409185 Down
hsa-miR-1306-5p 43.10136 19.03914 1.178765 Down
hsa-miR-141-3p 412.5014 195.7189 1.075616 Down
hsa-miR-9-5p 753.6843 363.8622 1.050568 Down
hsa-miR-10a-5p 87953.51 42629.77 1.04488 Down
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2048 European Journal of Applied Physiology (2023) 123:2041–2051
1 3
expressed EV-miRNAs were screened out. It was found
that 70 miRNAs changed differentially after exercise, 45
miRNAs were up-regulated, and 25 miRNAs were down-
regulated. By screening the five target genes of miR-144-3p,
miR-145-3p, miR-509-5p, miR-891b, and miR-890 with the
largest fold change, functional enrichment analysis showed
that the target genes are involved in the regulation of LTP,
VEGF, glutathione metabolism pathway, dopaminergic syn-
apse, signal transmission, biological regulation, and other
biological processes. Our data suggested that the miRNA
profiles of circulating extracellular vesicles could be modi-
fied by a single session of fatiguing swimming, and that
EV-miRNAs might be involved in the mechanisms related
to adaptation to fatiguing exercise.
During the full 1500-m freestyle swimming, the serum
CK value reached 340U/L, while the blood lactate reached
11.2mmol/L. These results show that the subjects had gone
all out for the full 1500-m freestyle swimming. This study
also confirmed that going all out for the full 1500-m free-
style swimming can cause exercise-induced fatigue. The
RPE scale reached above 19, sports ability decreased, physi-
cal function declined, and other fatigue indicators signifi-
cantly changed. Skeletal muscle is the main place for lactate
production, and accumulation of lactate may be related to
Fig. 5 Differentially expressed
EV-miRNAs GO function clas-
sification map
Fig. 6 Differentially expressed
EV-miRNAs target gene KEGG
signaling pathway enrichment
map
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2049European Journal of Applied Physiology (2023) 123:2041–2051
1 3
the calcium signal pathway regulated by EV-miRNAs, which
in turn might be involved in the blockade of neuromuscular
conduction (Brooks 2020).
It is interesting to note that the characteristics of EV-miR-
NAs were modified after a single session of fatiguing swim-
ming. A large number of EVs were released, and the CD63
and ALIX-labeled proteins were significantly expressed in
the subjects’ plasma. Similar results have been reported
in the literature: the expression of EVs markers Tsg101,
HSP70, CD63, and Flot-1 increased immediately following
EV release after exercise on power bicycles and treadmills,
and returned to baseline after 90min of recovery (Frühbeis
etal. 2015). The same phenomenon was also observed in
a study of exhaustive treadmill tests (Helmig etal. 2015;
Karine etal. 2018); importantly, the study also observed
the expression of various miRNAs in EVs after exercise.
Another study found that miR-128-3p, miR-103-3p, miR-
330-5p, miR-148a-3p, miR-191a-5p, miR-10b-5p, miR-
93-5p and miR-25-3p in EVs have significant differential
expression after acute exercise (Oliveira Getúlio etal. 2018).
In this study, it was found that five EV-miRNAs were sig-
nificantly differentially expressed after fatiguing swimming;
three miRNAs of miR-144-3p, miR-145-3p, miR-509-5p had
been up-regulated, and two miRNAs of miR-891b and miR-
890 down-regulated. Studies have shown that the changes of
miRNA and proteins carried by circulating exosomes help
the body cope with the stress of acute fatigue exercise (Nair
etal. 2020). Differentially expressed EV-miRNAs might
inhibit the post-transcriptional translation process by inhib-
iting mRNAs and have biological effects in the process of
fatigue (Assmann etal. 2019; Görgens etal. 2015).
Of the five EV-miRNAs differentially expressed after the
fatiguing swimming, MiR-144-3p is related to a variety of
biological processes, including nerve function, angiogene-
sis, adipogenesis, bone metabolism, and tumorigenesis (Lan
etal. 2015; Liu etal. 2016; Sun etal. 2017); MiR-145-3p
is involved in the regulation of VEGF related to angio-
genesis and LTP related to nerve function; miR-509-5p is
related the GnRH signaling pathway, which is associated
with the potential signal pathways of fatigue. The down-
regulation of miR-891b expression can inhibit the expression
of GADD45β and Lnc-IRAK3-3, which can improve the
body's antiviral immunity (Liao etal. 2019). Many studies
have shown that the miRNAs carried by exercise-released
EVs mediate cell-to-cell communication, participate in the
regulation of energy metabolism during exercise, which have
been identified as novel players in promoting systemic ben-
eficial effects (Brisamar etal. 2020; Rong etal. 2020).
Through bioinformatics analysis, it was found that the
main enriched biological processes of target genes that
differentially express EV-miRNAs include regulation of
metabolic processes, neuromuscular signal transmission,
central nervous system regulation, and biological regulation
involving EVs. Through KEGG functional enrichment
analysis, it was found that the target genes that differen-
tially express EV-miRNAs are mainly involved in meta-
bolic pathways, VEGF, LTP, dopaminergic and cholinergic
synapse, calcium signaling pathway, glutathione, glycer-
ophospholipid, and arachidonic acid metabolism, and many
other pathways. The LTP signaling pathway, dopaminergic
synaptic pathway, and cholinergic synapse involved in the
regulation of the target genes can improve brain synaptic
plasticity, improve brain cognitive and executive functions,
and promote the recovery of neurological function. It can
thus be suggested that the differential EV-miRNAs involve
the adaptation to a single fatiguing swimming session
(D’Souza etal. 2017). A recent study showed that after acute
aerobic exercise, the expression level of exosomal miRNAs
(miR206, miR133b, and miR-181a-5p) increased (Oliveira
Getúlio etal. 2018). Bioinformatics pathway analysis shows
that exercise-induced exosomes are predicted to target
genes involved in the MAPK pathway to promote muscle
cell growth and differentiation. It can be seen that the up-
regulation of selective muscle-specific miRNAs in exosomes
may be related to the degree of muscle damage, thereby
promoting the process of muscle repair and regeneration
(Muroya etal. 2015). Therefore, after fatiguing swimming,
the characteristics of EV-miRNAs had changed to adapt to
exercise-induced physiological changes (Safdar and Tar-
nopolsky 2018). Differentially expressed miRNAs might
cross-regulate multiple biological information processes and
signaling pathways, indicating that exercise-induced EV-
miRNAs changes might play an important role in skeletal
muscle regulation and central nervous system regulation,
which participate in the process of fatigue.
Conclusions
The miRNA profile of EVs in plasma changed significantly
under the fatigue state after 1500-m freestyle swimming,
especially for miR-144-3p, miR-145-3p, miR-509-5p, miR-
891b, and miR-890. The changed EV-miRNAs might be
involved in the mechanisms related to adaptation to fatigu-
ing exercise, and can provide theoretical support for targeted
prevention of exercise-induced fatigue.
Limitations
A number of limitations of this study should be considered.
The study design lacked appropriate rest and non-fatiguing
exercise controls, so the present findings cannot be solely
ascribed to the impact of the fatiguing 1500m freestyle
swimming. In addition, only male athletes were included
in this study.
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2050 European Journal of Applied Physiology (2023) 123:2041–2051
1 3
Acknowledgements The authors wish to thank all participants, teach-
ers from the Key Laboratory of Sports Biochemical Chemistry, Guang-
zhou Sport University, Prof. Xiquan Weng for revising the grammar
and style of the manuscript, Weiwei Huang for their participation in
the study.
Author contributions Conceptualization, ZJL, WTL, and GQX; meth-
odology, ZJL, and GQX; software, ZJL and GQX; validation, GQX,
and WTL; formal analysis, ZJL, WTL, and GQX; investigation, ZJL
and GQX; resources, WTL, and GQX; data curation, ZJL and GQX;
writing-original draft preparation, ZJL, and XBC; writing-review and
editing, WTL, XY, XBC and GQX; visualization, WTL, XY and GQX;
supervision, WTL, and GQX; project administration, GQX. All authors
have read and agreed to the published version of the manuscript.
Funding This research was funded by the Characteristic Innovation
Projects of Ordinary Colleges and Universities of Guangdong, China,
grant number No. 2020KTSCX065 and the National Innovation and
Entrepreneurship Projects of College Students, China, Grant number
No. 5200080449. The APC was funded by Characteristic innovation
projects of ordinary colleges and universities of Guangdong, China.
Data availability The datasets for this study are available as [raw
data20220606.zip] at https:// figsh are. com/ artic les/ datas et/ raw_ data2
02206 06_ zip/ 20029 349.
Declarations
Conflict of interest All authors declare no conflict of interest.
Ethical approval The study was approved by the Guangzhou Sports
University Ethics Committee (Approval No. 2020LCLL-006).
Informed consent Informed consent was obtained from all subjects
involved in the study. Written informed consent to participate in this
study was provided by the participants.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article's Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
the article's Creative Commons licence and your intended use is not
permitted by statutory regulation or exceeds the permitted use, you will
need to obtain permission directly from the copyright holder. To view a
copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/.
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