Abstract
Introduction
Advanced glycation end products (AGEs) play a critical role in the
development of vascular diseases in diabetes. Although stem cell
therapies often involve exposure to AGEs, the impact of this
environment on extracellular vesicles (EVs) and endothelial cell
metabolism remains unclear.
Methods
Human umbilical cord mesenchymal stem cells (MSCs) were treated with
either 0 ng/ml or 100 ng/ml AGEs in a serum-free medium for 48 hours,
after which MSC-EVs were isolated. The EVs were characterized by
morphology, particle size, and protein markers of MSC-EVs, and microRNA
(miRNA) sequencing was performed to identify differentially expressed
miRNAs. MSC-EVs were cocultured with human umbilical vein endothelial
cells (HUVECs) to assess effects on cell viability, metabolic activity,
oxidative stress, and antioxidant capacity. Tube formation and glucose
transporter protein analyses were conducted to evaluate the angiogenic
ability and glucose metabolism capacity.
Results
MSC-EVs ranged from 30 to 150 nm, which is consistent with exosomal
properties. AGEs treatment reduced MSC viability but had minimal effect
on EV morphology and protein markers. miRNA sequencing showed
downregulation of hsa-miR-223-3p and hsa-miR-126-3p_R-1, with
upregulation of hsa-miR-574-5p, implicating changes in glycolytic and
oxidative phosphorylation pathways. MSC-EVs treated with AGEs decreased
HUVEC viability (P < 0.05), pH (P < 0.05), adenosine triphosphate (ATP)
metabolism (P < 0.05), glucose metabolism (P < 0.05), while enhancing
glycolysis processes, including glycolytic activity, capacity, and
reserve (P < 0.05). This likely resulted from impaired mitochondrial
function, including reduced ATP production, maximal respiration, basal
respiration, and spare respiratory capacity (P < 0.05), or increased
reactive oxygen species (ROS) (P < 0.05) and glucose-6-phosphate
dehydrogenase (G6PD) activity (P < 0.05). In addition, AGEs reduced
glucose transporter types 1, 3, and 4 (GLUT1, GLUT3, GLUT4), and
synthesis of cytochrome c oxidase 2 expression (P < 0.05), along with
angiogenic capacity (P < 0.05) in HUVECs.
Conclusion
Exposure to AGEs diminishes the therapeutic potential of MSC-derived
EVs by disrupting energy metabolism and promoting metabolic
reprogramming in endothelial cells. These findings suggest that
adjusting the dosage or frequency of MSC-EVs may enhance their efficacy
for treating diabetes-related vascular conditions. Further research is
warranted to evaluate AGEs' broader impact on various cell types and
metabolic pathways for improved exosome-based therapies.
Keywords: advanced glycation end products, angiogenesis, energy
metabolism, extracellular vesicles, mesenchymal stem cells, oxidative
stress
Graphical abstract
[45]graphic file with name ga1.jpg
[46]Open in a new tab
__________________________________________________________________
AGEs play a significant role in the development of complications
associated with diabetes and cardiovascular diseases. These compounds
are produced through nonenzymatic reactions involving sugars and
proteins, lipids, or nucleic acids, and they accumulate in the body,
initiating various pathophysiological responses that lead to tissue
damage and functional impairment.[47]1, [48]2, [49]3 For example, upon
binding to their receptor (RAGE), the cytoplasmic domain of RAGE
engages with diaphanous-related formin-1 and formin homology 1 domain,
activating Rho GTPases Rac-1 and Cdc42.[50]^4 This activation then
leads to the initiation of the c-jun n-terminal kinase and p38
mitogen-activated protein kinase pathways,[51]^5 which in turn
stimulate the proinflammatory transcription factors nuclear factor
kappa-light-chain-enhancer of activated B cells[52]^6^,[53]^7 and
activator protein-1.[54]^8 Nuclear factor kappa-light-chain-enhancer of
activated B cells subsequently move into the nucleus, driving the
expression of various proinflammatory genes, such as interleukin (IL)-6
and tumor necrosis factor-alpha, along with adhesion molecules such as
vascular cell adhesion molecule-1.[55]^9 Furthermore, the AGE/RAGE
interaction, through a protein kinase C–dependent mechanism, recruits
adaptor proteins myeloid differentiation primary response 88 and
toll-IL-1 receptor adaptor protein to form a signaling complex that
transmits signals to downstream targets.[56]^10 Through this toll-IL-1
receptor adaptor protein/myeloid differentiation primary response 88
complex, RAGE ligands activate protein kinase B, which sustains nuclear
factor kappa-light-chain-enhancer of activated B cell activation,
thereby intensifying the inflammatory response.[57]^11 The binding of
AGE to RAGE on the cell surface increases the expression of
nicotinamide adenine dinucleotide phosphate (NADPH) oxidase subunits,
which activates NADPH oxidase[58]^12 and fosters ROS generation.[59]^13
These ROS induce oxidation and nitrosylation of proteins, resulting in
cellular damage and disruption of enzymatic functions.[60]^14 The
initial ROS produced further stimulate mitochondrial ROS production,
causing a cascade of oxidative reactions within the cell.[61]^2 The
accumulation of ROS leads to oxidative damage to lipids, proteins, and
DNA, resulting in changes to the structure and function of endothelial
cells.[62]^15
Pathological alterations inflict harm upon vascular endothelial cells,
promote the proliferation and migration of cells, cause intimal
thickening, and accelerate the development of atherosclerosis.[63]^16
In addition, AGEs can cross-link extracellular matrix proteins such as
collagen and elastin, resulting in matrix stiffening and vascular
rigidity. It compromises vascular elasticity and function.[64]^17 In
diabetic retinopathy, AGEs accumulate in retinal microvessels, damaging
retinal vessels and cells, and causing retinopathy.[65]^18 Recent
studies highlighted a bidirectional feedback mechanism between cardiac
structural remodeling and mitochondrial bioenergetic function,[66]^19
and improving mitochondrial function can prevent diabetic
nephropathy.[67]^20 Thus, mitochondrial metabolic function is crucial
for the prevention and treatment of diabetes and cardiovascular
diseases.
MSCs and their secreted vesicles have demonstrated remarkable potential
in vascular repair and functional regulation.[68]^21^,[69]^22 MSCs are
multipotent stem cells capable of self-renewal and differentiation into
various cell types. Meanwhile, their vesicles act as crucial mediators
of intercellular communication, carrying numerous bioactive molecules
including proteins, RNA, and miRNAs.[70]^23^,[71]^24 Studies have shown
that EVs-MSC are rich in angiogenic factors such as vascular
endothelial growth factor, fibroblast growth factor-2, and
angiopoietin-1.Then they substantially boost endothelial cell
proliferation and angiogenesis.[72]^25 In animal models, MSC-EVs have
exhibited significant therapeutic effects. For example, they promote
angiogenesis and improve mitochondrial function in models of diabetic
foot ulcers and diabetic nephropathy.[73]^26^,[74]^27 Certain miRNAs,
such as miR-126 and miR-210, are enriched in MSC vesicles,[75]^28 and
these miRNAs can modulate inflammatory and oxidative stress responses,
affecting mitochondrial function, reducing endothelial cell damage, and
maintaining vascular function.[76]^29^,[77]^30
Therefore, the utilization of MSC vesicles in addressing diabetic
complications and vascular diseases holds a significant promise.
Nevertheless, when treating these conditions, MSCs are often exposed to
an environment rich in AGEs.[78]^31 The impact of this environment
remains largely unknown on the morphology, quantity, and miRNA
production of EVs-MSC, as well as on mitochondrial function and energy
metabolism in endothelial cells. This study, through high-throughput
miRNA sequencing analysis, investigates the effects of AGEs on MSC
vesicles and their influence on the metabolic activity and function of
vascular endothelial cells. The insights gained will assist in
assessing the metabolic alterations prompted by stem cell vesicles
therapy in diabetes and cardiovascular diseases, providing theoretical
guidance for the practical application of MSC EVs.
Methods
Cell Culture
Human umbilical cord MSCs were obtained from XIAMEN Anti-hela
Biological Technology Trade Co. Ltd (Xiamen, China). To assess the
effects of AGEs on cell viability, MSCs were treated with 0 ng/ml, 50
ng/ml, 100 ng/ml, 200 ng/ml, and 400 ng/ml of AGEs (bs-1158P, Bioss)
for 48 hours. AGEs were naturally purified proteins with a purity >
98%. The lyophilized protein was dissolved in 10mM phosphate-buffered
saline (PBS) (pH 7.4) and diluted according to the desired
concentration; avoid repeated freeze/thaw cycles were avoided.
We inoculated 1×10^7 MSCs into a 3D FloTrixTM miniSPIN bioreactor
(CytoNiche, miniSPIN S1-01) containing 200 ml culture medium, at 37 °C
in a 5% CO₂ incubator. After 48 hours, they were replaced with
serum-free human umbilical cord MSCs (IMMOCELL, IML-103-1) supplemented
with final concentrations of 0 ng/ml and 100 ng/ml AGEs for 48 hours.
Removed the bioreactor and allowed the microcarriers with cells to
settle. Collected the supernatant to extract EVs. This study was
divided into the following 3 groups:
* •
Mock: HUVECs were cultured in complete endothelial cell medium
(IMC-309, IMMOCELL) for 48 hours.
* •
EVs-MSC: HUVECs were cocultured with 5 μg/96-well, 20 μg/24-well,
80 μg/6well EVs derived from MSCs treated with 0 ng/ml AGEs in
complete medium for 48 hours.
* •
EVs-MSC/AGEs: HUVECs were cocultured with 5 μg/96-well, 20
μg/24-well, 80 μg/6well EVs derived from MSCs treated with 100
ng/ml AGEs in complete medium for 48 hours.
EVs Extraction and Characterization
EVs were extracted by ultracentrifugation (Hitachi, CP100MX). First,
the samples were transferred into a new centrifuge tube and centrifuge
at 2000 g for 30 minutes at 4 °C; then carefully transferred the
supernatant to a new tube and centrifuged again at 10,000 g for 45
minutes at 4 °C to remove larger vesicles. The supernatant was filtered
through a 0.45 μm filter (Millipore, R6BA09493), collecting and
transferring the filtrate to a new tube, then was centrifuged at
100,000g for 70 minutes at 4 °C. Discarded the supernatant, resuspended
the pellet in 10 ml of 1× PBS (Sangon Biotech, E607008), and repeated
ultracentrifugation at 100,000 g for another 70 minutes at 4 °C. The
supernatant was removed, resuspended in 100 μl PBS, 20 μl for
transmission electron microscopy, 10 μl for nanoparticle tracking
analysis, and the remaining exosomes were stored at −80 °C.
Exosome characterization was performed using nanoparticle tracking
analysis to determine particle size and concentration, transmission
electron microscopy to observe exosome morphology and structure, and
Western blotting to detect exosome marker proteins (such as
differentiation [CD]9, CD63, and CD81) to confirm purity and
characteristics. The concentration of EVs was determined using the BCA
protein quantification assay kit (KGB2101, Keygen).
3-(4,5-Dimethylthiazol-2-yl)-2,5-Diphenyltetrazolium Bromide Proliferation
Assay and pH Measurement
After treating the cells according to the specified groups, 20 μl of
3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide solution
(40201ES72, Yeasen) was added to each well and incubated for 4 hours.
The supernatant was then discarded, and 150 μl of dimethyl sulfoxide
was added to dissolve the formazan crystals by shaking for 10 minutes.
The optical density was measured at 490 nm (MOLECULAR), and the
relative cell viability was calculated based on the results.
For pH measurement, the supernatant was collected after treatment, and
the pH was measured using a Leici pH meter (PHS-3C), with the values
recorded.
ROS and 5,5',6,6'-Tetrachloro-1,1',3,3'-Tetraethylbenzimidazolylcarbocyanine
Iodide (JC-1) Flow Cytometry Detection
After treating the cells according to the groups, ROS detection was
performed using the ROS assay kit (50101ES01, Yeason). Cells were
collected by centrifugation at 300 g for 5 minutes at 4 °C and
resuspended in serum-free medium at a density of 1.0×10^6 to 2.0×10^7
cells/ml. The cells were incubated with the DCFH-DA probe at a final
concentration of 10 μM in the dark for 20 minutes, mixing every 3 to 5
minutes. After washing the cells 1 to 2 times with serum-free medium,
they were resuspended in 500 μl of serum-free medium and analyzed by
flow cytometry.
For JC-1 mitochondrial membrane potential (mΔψm) detection, cells were
collected after treatment, and 100,000 to 600,000 cells were
resuspended in 0.5 ml of cell culture medium. JC-1 staining working
solution (0.5 ml) was added, and the cells were incubated at 37 °C for
20 minutes. Cells were then centrifuged at 600 g for 3 to 4 minutes at
4 °C, the supernatant was discarded, and cells were washed twice with
1 × JC-1 staining buffer, each time centrifuging at 600 g for 3 to 4
minutes at 4 °C. Finally, the cells were resuspended in an appropriate
amount of 1× JC-1 staining buffer and analyzed by flow cytometry to
calculate the relative MFI (Green/Red).
Metabolic Function Detection
ATP Detection
After group treatments, the culture medium was removed, and 200 μl of
lysis buffer (S0026, Beyotime) was added to each well to lyse the
cells. The lysates were centrifuged at 12,000 g for 5 minutes at 4 °C,
and the supernatant was used for ATP detection. The ATP detection
reagent was dissolved on ice, and the ATP standard solution was diluted
to concentrations of 0.01, 0.03, 0.1, 0.3, 1, 3, and 10 μM. After
preparing the ATP detection working solution, 100 μl was added to each
well and left to sit for 3 to 5 minutes to consume the background ATP.
Then, 20 μl of the sample or standard was added, mixed well, and the
relative light units or counts per minute was measured using a
chemiluminescence detector. The ATP concentration in the samples was
calculated based on the standard curve.
G6PD Detection
After group treatments, the cells were collected in centrifuge tubes,
the supernatant was discarded, and 1 ml of extraction buffer (BC0260,
Solarbio) was added. The cells were disrupted by ultrasonication (20%
power, sonicate for 3 seconds, rest for 10 seconds, repeated 30 times).
The lysates were centrifuged at 8000g for 10 minutes at 4 °C, and the
supernatant was collected and kept on ice for analysis. The ultra
violet spectrophotometer was preheated for more than 30 minutes, and
the wavelength was set to 340 nm, with distilled water as the blank.
Reagent 1 was preheated in a 37 °C water bath for 30 minutes. A working
solution (950 μl) was mixed with 50 μl of the sample or distilled
water, and the absorbance change at 340 nm was measured over 5 minutes.
The absorbance at 0 seconds was recorded as A1 and at 300 seconds as
A2. The change in absorbance (ΔA) was calculated as ΔA_sample =
A2_sample − A1_sample; and ΔA_blank = A2_blank − A1_blank. The G6PDH
activity units were calculated using the following equation:
[MATH: G6PDH(U/104cel
l)=[(ΔAsample−ΔAblank)÷(ε×d)×109×Vreaction]÷(Vsample÷Vextraction×500)÷T=1.286×(ΔAsample−ΔAblank) :MATH]
Glucose Detection
The glucose test strip (Sannuo) was removed and the electrode end was
inserted into the glucometer (GA-3 model, Sannuo); 200 μl of the
treated supernatant was placed in a glass dish; the suction port was
brough to the top end of the test strip into contact with the
supernatant. The sample was automatically drawn into the reaction
chamber of the test strip; and the measurement value recorded.
Lactic Acid Detection
After treatment, cells were lysed using PBS as a homogenization medium
and centrifuged to collect the supernatant for measurement. The enzyme
working solution and color reagent were prepared according to the
lactate (LD) assay kit (A019-2-1, Nanjing Jiancheng). For each tube,
the system included 1 ml of enzyme working solution, 0.2 ml of color
reagent, and 0.02 ml of distilled water per 3 mmol/l standard per
sample. The system was mixed well and incubated at 37 °C for exactly 10
minutes in a water bath; 2 mL of stop solution was added, mixed well,
and the absorbance (A) of each sample at a wavelength of 530 nm was
measured. Then 200 μl of the reaction mixture was transferred to a
96-well plate for absorbance measurement. The calculation formula was
as follows:
[MATH: LD(mmol/gpro
t)=Asa<
mi>mple−Abla
nkAstandard−Abla
nk×Cstandard÷Cpr :MATH]
Seahorse
Cell Mitochondrial Stress Test
Seahorse XFe/XF analyzer was preheated for at least 5 hours. Cells were
seeded into the Seahorse XF cell culture microplate and incubated in a
37 °C, CO2-free incubator. A sensor probe plate was hydrated with
Seahorse XF calibrant overnight. The next day, the assay medium was
prepared by supplementing Seahorse XF Dulbecco's Modified Eagle medium
with additives (1 mmol/l sodium pyruvate, 2 mmol/l glutamine, and 10
mmol/l glucose). The assay medium warmed to 37 °C in a water bath.
Oligomycin (blue cap), carbonyl
cyanide-p-trifluoromethoxyphenylhydrazone (yellow cap), and
rotenone/antimycin A (red cap) compounds were retrieved from the
Seahorse XF Cell Mito Stress Test Kit, the compounds in the assay
medium dissolved, 2 to 3 ml of working solution prepared, and added to
the injection ports on the probe plate. According to the manual, the
recommended starting volume of assay medium for a 96-well cell plate
was 180 μl per well. The Seahorse XF cell culture microplate was
removed from the incubator, confluency confirmed, the culture medium
replaced with prewarmed assay medium, and the cell culture microplate
incubated in a 37 °C CO2-free incubator for 45 minutes. Finally, the
calibration plate and the probe plate with compounds were placed into
the instrument's tray for calibration and analysis.
Cellular Glycolytic Stress Test
The Agilent Seahorse XFe/XF analyzer was preheated for at least 5
hours. Cells were seeded at a predetermined optimal density into the
Seahorse XF cell culture microplate using the appropriate cell growth
medium (containing the corresponding EVs). A sensor probe plate was
hydrated with Seahorse XF calibrant overnight in a CO2-free incubator.
The next day, the assay medium was prepared with 2 mmol/l glutamine as
the starting condition, the pH adjusted to 7.4 using 0.1 N NaOH, and
warmed to 37 °C for use. Oligomycin (light blue cap), glucose (blue
cap), and 2-deoxyglucose (green cap) were retrieved from the Seahorse
XF Glycolysis Stress Test Kit, dissolved in the assay medium, and added
to the appropriate injection ports on the hydrated probe plate. They
were then added as indicated in [79]Table 1. The Seahorse XF cell
culture microplate was removed from the incubator, cell confluency
confirmed, the culture medium was replaced with prewarmed assay medium
and incubate the cell culture microplate was incubated in a 37 °C,
CO2-free incubator for 45 minutes. Finally, the calibration plate and
the probe plate with the compounds were placed into the instrument's
tray for calibration and analysis.
Table 1.
Cellular glycolytic stress test volume instruction
Agilent Seahorse XFe/XF96 Fixed volume
__________________________________________________________________
Fixed concentration
__________________________________________________________________
Initial well volume: 175 μl assay medium Initial well volume: 180 μl
assay medium
Injection Port A
Glucose Final Well Concentration (mmol/l) Stock Solution Volume (μl)
Assay Medium Volume (μl) 8X (Injection Port Volume (μl) Added to
Injection Port Volume (μl) Final Well Concentration (mmol/l) Stock
Solution Volume (μl) Assay Medium Volume (μl) 10X (Injection Port
Volume [μl]) Added to Injection Port Volume (μl)
10 3000 750 80 25 10 3000 0 100 20
Injection Port B
Oligomycin Final Well Concentration (mmol/l) Stock Solution Volume (μl)
Assay Medium Volume (μl) 9X (Injection Port Volume [μl]) Added to
Injection Port Volume (μl) Final Well Concentration (mmol/l) Stock
Solution Volume (μl) Assay Medium Volume (μl) 10X (Injection Port
Volume [μl]) Added to Injection Port Volume (μl)
1.0 270 2730 9 25 1.0 300 2700 10 22
Injection Port C
2-DG Final Well Concentration (mmol/l) Stock Solution Volume (μl) Assay
Medium Volume (μl) 10X (Injection Port Volume [μl]) Added to Injection
Port Volume (μl) Final Well Concentration (mmol/l) Stock Solution
Volume (μl) Assay Medium Volume (μl) 10X (Injection Port Volume [μl])
Added to Injection Port Volume (μl)
50 3000 0 500 25 50 3000 0 500 25
[80]Open in a new tab
2-DG, 2-deoxyglucose.
RT-Quantitative Polymerase Chain Reaction
Total RNA was extracted from samples using the Trizol method, and its
quality was assessed. RNA was then reverse-transcribed into cDNA using
the HiScript II Q RT SuperMix (R222-01, Vazyme Biotech, Nanjing). The
quantitative polymerase chain reaction system was prepared, including
cDNA template, specific primers, and fluorescent dye (Q431-02, Vazyme
Biotech, Nanjing); and amplification was performed on a quantitative
polymerase chain reaction instrument. The relative expression levels of
target genes were calculated using the ΔΔCt method by analyzing the Ct
values. The reference gene and target gene primer information were
shown in [81]Table 2.
Table 2.
Primer sequence
The reference gene Upstream primer sequences (5 ′ −3 ′) Downstream
primer sequences (5 ′ −3 ′)
18S CGACGACCCATTCGAACGTCT CTCTCCGGAATCGAA CCCTGA
GLUT3 TGCCTTTGGCACTCTCAACCAG GCCATAGCTCTTCAGACCCAAG
GLUT1 TTGCAGGCTTCTCCAACTGGAC CAGAACCAGGAGCACAGTGAAG
GLUT4 CCATCCTGATGACTGTGGCTCT GCCACGATGAACCAAGGAATGG
SCO2 GACCACTCCATTGCCATCTACC CTCAAGACAGGACACTGCGGAA
[82]Open in a new tab
GLUT, glucose transporter type; SCO2, synthesis of cytochrome c
oxidase 2.
Western Blot (WB)
Proteins were extracted from cells using lysis buffer and centrifuged
at 12,000 g for 30 minutes. The supernatant was collected, and protein
concentration was determined using a BCA assay kit. Proteins were
separated by SDS-PAGE electrophoresis and then transferred from the gel
to a PVDF membrane. The membrane was blocked with 5% BSA at room
temperature for 1 hour, incubated with specific primary antibodies
overnight at 4 °C, and then with HRP-conjugated secondary antibodies.
Finally, the protein bands were visualized using chemiluminescent
reagents (e.g., ECL), and recorded and analyzed using an imaging
system. The dilution ratios for the primary antibodies were: GLUT1
(21829-1-AP, Proteintech) 1:500, GLUT3 (ab314193, Abcam) 1:500,
synthesis of cytochrome c oxidase 2 ([83]Ab169042, Abcam) 1:500, and
GLUT4 (ab313775, Abcam) 1:500; Actin (SA00001-1, Proteintech) 1:1000.
The secondary antibodies HRP-Anti-Rat IgG (SA00001-2, Proteintech) and
HRP-Anti-Mouse IgG (SA00001-1, Proteintech) were diluted 1:10000. The
original western blot is shown in [84]Supplementary Figure S1.
Tube Formation Assay
The day before the experiment, Matrigel was thawed overnight at 4 °C,
and pipette tips, 96-well plates, and centrifuge tubes were precooled.
Matrigel was diluted with Dulbecco's Modified Eagle medium at a 1:1
ratio, and 50 μl of Matrigel was added to each well of the precooled
96-well plate. The plate was incubated at 37 °C for 45 minutes to 1
hour to solidify the Matrigel. Cells were digested at 70% confluency,
washed with PBS, digested with trypsin, resuspended in
exosome-containing medium, and counted. The cell suspension was
adjusted to 50 μl per well (30,000 cells/well), with triplicates for
each group, and incubated at 37 °C or 5% CO2 for 3 hours. Finally, tube
formation images were captured using 40× and 100× magnifications.
miRNA Sequencing and Differential Analysis
Total RNA of high purity was extracted from 2 types of EVs. The small
RNA library was constructed using an end repair, adaptor ligation,
reverse transcription, and polymerase chain reaction amplification kit.
The constructed library was sequenced on a high-throughput sequencing
platform (Illumina HiSeq). The sequencing data underwent quality
control, adaptor removal, and low-quality read filtering. Clean reads
were aligned to the reference genome or known small RNA databases using
alignment tools. The expression levels of each miRNA were calculated
based on the alignment results, and differential expression analysis
tools (e.g., DESeq2 or EdgeR) were used to compare miRNA expression
levels between different groups, identifying significantly
differentially expressed miRNAs. Functional annotation and pathway
analysis were performed on these differentially expressed miRNAs to
predict their target genes and explore their biological functions.
Statistical Analysis
The statistical analysis was performed using IBM SPSS Statistics,
version 26.0, available at
[85]https://www.ibm.com/products/spss-statistics. The data
visualization was carried out using GraphPad Prism, version 9.0,
available at [86]https://www.Gr.with. Results are presented as mean ±
SEM, with a minimum of 3 independent replicates per group. For
comparisons between 2 groups, a 2-tailed t test was employed. For
multiple group comparisons, 1-way analysis of variance was conducted,
followed by Tukey’s post hoc test for pairwise comparisons. A P-value <
0.05 was considered statistically significant; and results were denoted
as nonsignificant P > 0.05, ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001 and
∗∗∗P < 0.0001, where applicable.
Results
Characterization of AGE-treated EVs-MSC and the Cell Viability of MSC
As the concentration of AGEs increased (0, 50, 100, 200, 400 ng/ml),
the cell viability of MSCs significantly decreased. High concentrations
of AGEs (200 and 400 ng/ml) significantly reduced cell viability (P <
0.01); whereas low concentrations of AGEs (50 and 100 ng/ml) had no
significant effect on cell viability ([87]Figure 1a). We selected 100
ng/mL AGEs for subsequent experiments. The size distribution of EVs
from both groups was primarily between 40 and 100 nm, with the particle
size of EVs-MSC/AGEs being 47.87 nm, slightly smaller than that of
EVs-MSC, which was 56.78 nm ([88]Figure 1b). The particle sizes of
MSC-EVs range from 30 to 150 nm, classifying them as exosome. Both
EVs-MSC and EVs-MSC/AGEs expressed exosome marker proteins (CD9, CD81,
CD63), regardless of AGEs treatment, suitable for comparative
experiments ([89]Figure 1c). The morphology of EVs was similar in both
groups, with EVs-MSC/AGEs slightly oval and EVs-MSC more spherical
([90]Figure 1d). In summary, AGEs treatment reduced MSC cell viability
but minimally affected EV particle size, distribution, morphology, and
characteristic proteins.
Figure 1.
[91]Figure 1
[92]Open in a new tab
Characterization of AGE-treated EVs-MSC and the cell viability of MSC.
(a) Cell viability of MSCs treated with different concentrations of
AGEs (0, 50, 100, 200, 400 ng/ml) for 48 hours. ns: P > 0.05, ∗∗: P <
0.01. Compared to 0 ng/ml, 200 and 400 ng/ml significantly reduced cell
viability. (b) Nanoparticle tracking analysis showed the size
distribution of extracellular vesicles. (c) Western blot analysis of
exosome markers (CD9, CD81, CD63) in EVs-MSC and EVs-MSC/AGEs, with
actin as the loading control. (d) Transmission electron microscopy
(TEM) images showing the morphology and size of EVs-MSC and
EVs-MSC/AGEs at different magnifications (1 μm, 100 nm, 200 nm, 500
nm). AGEs, advanced glycation end products; EVs, extracellular
vesicles; MSC, mesenchymal stem cells; ns, nonsignificant.
Effects of AGE-Treated EVs-MSC on HUVEC Proliferation and Metabolic State
This study examined the impact of EVs-MSC and EVs-MSC/AGEs on HUVEC
cell viability and metabolism. Compared to the Mock group, EVs-MSC
significantly increased HUVEC cell viability (P < 0.01), ATP content
(P < 0.05), and glucose consumption (P < 0.05), with no significant
effects on pH, lactate production, or mΔψm in HUVECs (P > 0.05).
However, EVs-MSC/AGEs treatment led to reduced cell viability (P <
0.001) ([93]Figure 2a), lower pH (P < 0.01) ([94]Figure 2b), decreased
ATP content (P < 0.001) ([95]Figure 2c) and glucose consumption (P <
0.001) ([96]Figure 2d), increased lactate production (P < 0.05)
([97]Figure 2e), and higher mΔψm in HUVECs (P < 0.001) ([98]Figure 2f).
These results suggested that AGE-treated EVs-MSCs impaired cell
viability, acidified the cellular environment, reduced energy
metabolism, and may promote glycolysis, potentially due to
mitochondrial dysfunction or increased cellular stress. The AGEs
environment diminished the positive effects of EVs-MSC on endothelial
cells and altered energy metabolism pathways.
Figure 2.
[99]Figure 2
[100]Open in a new tab
Effects of AGE-treated EVs-MSC on HUVEC proliferation and metabolic
state. (a) Cell viability of HUVECs. Compared to the Mock group,
EVs-MSC increased cell viability, EVs-MSC/AGE reduced this increase in
viability. (b) pH levels in the culture medium of HUVECs. Compared to
the Mock group, EVs-MSC had no difference in pH. Compared to EVs-MSC,
EVs-MSC/AGE had a significant reduction in pH. (c) ATP content in
HUVECs. Compared to the Mock group, EVs-MSC increased ATP content,
EVs-MSC/AGE reduced this increase in ATP content. (d) Glucose
consumption of HUVECs. Compared to the Mock group, EVs-MSC increased
glucose consumption, EVs-MSC/AGE reduced this increase in glucose
consumption. (e) Lactic acid levels in the culture medium of HUVECs.
Compared to the Mock group, EVs-MSC had no difference in Lactic acid
levels. Compared to EVs-MSC, EVs-MSC/AGE had a significant increase in
Lactic acid levels. (f) Mitochondrial membrane potential (mΔψm) in
HUVECs. Compared to the Mock group, EVs-MSC had no difference in mΔψm.
Compared to EVs-MSC, EVs-MSC/AGE had a significant increase in mΔψm.
(g) Flow cytometry analysis of JC-1 fluorescence in HUVECs treated with
mock, EVs-MSC, or EVs-MSC/AGEs. ns: P > 0.05, ∗P < 0.05, ∗∗P < 0.01,
∗∗∗P < 0.001. AGEs, advanced glycation end products; ATP, adenosine
triphosphate; EVs, extracellular vesicles; HUVEC, human umbilical vein
endothelial cells; JC-1,
5,5',6,6'-Tetrachloro-1,1',3,3'-tetraethylbenzimidazolylcarbocyanine
iodide; MSC, mesenchymal stem cells.
Effects of AGE-Treated EVs-MSC on Glycolytic Metabolic Activity in HUVECs
The glucose concentration and lactate accumulation levels suggested
that AGE-treated EVs-MSC might promote the glycolysis process in
HUVECs. We used the Seahorse XF Glycolysis Stress Test to observe the
effects of EVs-MSC/AGEs on the glycolytic function of HUVECs in
real-time ([101]Figure 3a). The real-time extracellular acidification
rate curve showed that the glycolytic activity of EVs-MSC/AGEs was
markedly elevated post–glucose addition, compared to HUVEC control
group (P < 0.0001), whereas there was no significant difference
compared to the EVs-MSC group (P = 0.5509) ([102]Figure 3b). After
adding oligomycin (an ATP synthase inhibitor), the glycolytic capacity
of EVs-MSC/AGEs remained significantly higher than the HUVEC control
group (P < 0.0001), with a nonsignificant difference compared to the
EVs-MSC control group (P = 0.2028) ([103]Figure 3c). Following the
addition of 2-deoxyglucose, a glycolysis inhibitor, the glycolytic
reserve of EVs-MSC/AGEs was significantly higher than that of the HUVEC
control group (P = 0.0005), with no significant difference compared to
the EVs-MSC control group (P = 0.2135) ([104]Figure 3d). These findings
indicated that AGE-treated MSC-EVs exhibited enhanced glycolytic
activity, glycolytic capacity, and glycolytic reserve, mainly affecting
cellular energy metabolism through the glycolysis pathway.
Figure 3.
[105]Figure 3
[106]Open in a new tab
Effects of AGE-Treated EVs-MSC on glycolytic metabolic activity in
HUVECs. (a) Extracellular acidification rate (ECAR) profile of HUVECs.
Measurements were taken following sequential injections of glucose,
oligomycin, and 2-deoxyglucose (2-DG). (b) Glycolysis rate of HUVECs.
Glycolysis rate was calculated from ECAR data following glucose
injection. Compared to the HUVEC group, EVs-MSC had no difference in
glycolysis rate (P = 0.5509). Compared to the HUVEC group, EVs-MSC/AGE
had a significant increase in glycolysis rate (P < 0.0001). (c)
Glycolytic capacity of HUVECs. Glycolytic capacity was calculated from
ECAR data following oligomycin injection. Compared to the HUVEC group,
EVs-MSC had no difference in glycolytic capacity (P = 0.2028). Compared
to the HUVEC group, EVs-MSC/AGE had a significant increase in
glycolytic capacity (P < 0.0001). (d) Glycolytic reserve of HUVECs.
Glycolytic reserve was calculated from ECAR data by subtracting the
glycolysis rate from the glycolytic capacity. Compared to the HUVEC
group, EVs-MSC had no difference in glycolytic reserve (P = 0.2135).
Compared to the HUVEC group, EVs-MSC/AGE had a significant increase in
glycolytic reserve (P = 0.0005). 2-DG, 2-deoxyglucose; AGEs, advanced
glycation end products; EVs, extracellular vesicles; HUVEC, human
umbilical vein endothelial cells; MSC, mesenchymal stem cells.
Effects of AGE-Treated EVs-MSC on Mitochondrial Function of HUVECs
The JC-1 flow cytometry assay indicated an increase in mΔψm. To further
investigate the impact of EVs-MSC/AGEs on the mitochondrial function of
HUVECs, we performed Seahorse XF Mitochondrial Stress Test. HUVECs
treated with EVs-MSC exhibited higher oxygen consumption rates,
especially reaching peak respiratory capacity following carbonyl
cyanide-p-trifluoromethoxyphenylhydrazone injection, indicating
enhanced mitochondrial function. In contrast, HUVECs treated with
EVs-MSC/AGEs showed lower oxygen consumption rates throughout process,
suggesting impaired mitochondrial function ([107]Figure 4a). The proton
leak (P < 0.0001), ATP production (P = 0.0002), maximal respiratory
capacity (P < 0.0001), basal respiration (P < 0.0001), and spare
respiratory capacity (P = 0.0379) were significantly higher in HUVECs
treated with EVs-MSC than in the control group, whereas these
parameters were significantly diminished in HUVECs treated with
EVs-MSC/AGEs (P < 0.05) ([108]Figure 4b–f). Seahorse XF analysis
results demonstrated that EVs-MSC significantly enhanced the
mitochondrial function of HUVECs, including ATP production, maximal
respiratory capacity, basal respiration, and spare respiratory
capacity. Conversely, EVs from an AGEs environment notably impaired
these metabolic functions. AGEs not only altered the metabolic
regulatory capacity of EVs but also decreased the mitochondrial
function of endothelial cells.
Figure 4.
[109]Figure 4
[110]Open in a new tab
Effects of AGE-treated EVs-MSC on mitochondrial function of HUVECs. (a)
Oxygen consumption rate (OCR) profile of HUVECs. Measurements were
taken following sequential injections of oligomycin, FCCP, and
rotenone/antimycin A (Rot/AA). (b) Proton leak of HUVECs. Compared to
the HUVEC group, EVs-MSC had significant increase in proton leak (P <
0.0001). Compared to the EVs-MSC, EVs-MSC/AGE had a significant
reduction in proton leak (P < 0.0001). (c) ATP production in HUVECs.
Compared to the HUVEC group, EVs-MSC had significant increase in ATP
production (P = 0.0002). Compared to the EVs-MSC, EVs-MSC/AGE had a
significant reduction in ATP production (P < 0.0047). (d) Maximal
respiration of HUVECs. Compared to the HUVEC group, EVs-MSC had
significant increase in maximal respiration (P < 0.0001). Compared to
the EVs-MSC, EVs-MSC/AGE had a significant reduction in maximal
respiration (P < 0.0001). (e) Basal respiration of HUVECs. Compared to
the HUVEC group, EVs-MSC had significant increase in basal respiration
(P < 0.0001). Compared to the EVs-MSC, EVs-MSC/AGE had a significant
reduction in basal respiration (P < 0.0001). (f) Spare respiratory
capacity of HUVECs Compared to the HUVEC group, EVs-MSC had significant
increase in spare respiratory capacity (P = 0.0379). Compared to the
EVs-MSC, EVs-MSC/AGE had a significant reduction in spare respiratory
capacity (P = 0.0141). AGEs, advanced glycation end products; ATP,
adenosine triphosphate; EVs, extracellular vesicles; FCCP, carbonyl
cyanide-p-trifluoromethoxyphenylhydrazone; HUVEC, human umbilical vein
endothelial cells.
Effects of AGE-Treated EVs-MSC on Oxidative Stress and Antioxidant Capacity
in HUVECs
An increase in mΔψm may also be attributed to excessive cellular
stress. We examined how EVs-MSC/AGEs impact oxidative stress and
antioxidant capacity in HUVECs by measuring ROS levels and G6PD
activity. The mock group showed baseline levels of ROS and G6PD
activity. EVs-MSC/AGEs significantly increased ROS levels (P < 0.0001)
and G6PD activity (P < 0.01) in HUVECs, whereas EVs-MSC had no
significant impact on ROS levels and G6PD activity ([111]Figure 5a–d).
G6PD is a key enzyme in the pentose phosphate pathway that generates
NADPH. NADPH helps maintain glutathione in its reduced state,
protecting cells from oxidative stress. Our results indicated that
EVs-MSC/AGEs induced intracellular oxidative stress, leading to an
upregulation of G6PD activity as a cellular response to elevated ROS
levels, thereby enhancing antioxidant capacity. This suggested that
AGE-treated EVs-MSC can induce metabolic reprograming to maintain redox
balance in HUVECs.
Figure 5.
[112]Figure 5
[113]Open in a new tab
Effects of AGE-treated EVs-MSC on oxidative stress and antioxidant
capacity in HUVECs. (a) Flow cytometry histograms showing ROS levels in
HUVECs treated with mock, EVs-MSC, and EVs-MSC/AGEs. ROS levels were
measured using the DCFDA assay, where DCF fluorescence indicates ROS
production. (b) Overlay of flow cytometry. (c) Quantification of
relative mean fluorescence intensity (MFI) of DCF in HUVECs. (d)
Glucose consumption of HUVECs. ns: P > 0.05, ∗∗P < 0.01, ∗∗∗P < 0.0001.
AGEs, advanced glycation end products; DCFDA, 2',7' -dichlorofluorescin
diacetate; EVs, extracellular vesicles; HUVEC, human umbilical vein
endothelial cells; MSC, mesenchymal stem cells; ns, nonsignificant.
Effects of AGE-Treated EVs-MSC on Angiogenic Capacity of HUVECs
Angiogenic capacity is crucial for addressing diabetic complications,
wound healing, and ischemic conditions. At 40× and 100× magnification,
HUVECs created sparse tubular structures with limited connections,
resulting in a nondense network. EVs-MSC treatment significantly
enhanced the tubulogenic capacity of HUVECs, creating more, continuous,
and denser tubular structures, indicating potent angiogenesis.
Conversely, EVs-MSC/AGEs treatment reduced this capacity, leading to
fewer and incomplete tubular structures with a sparser network than in
control and EVs-MSC alone ([114]Figure 6). These results suggested that
the AGEs environment negatively impacted exosome function, reducing
their angiogenic capacity.
Figure 6.
[115]Figure 6
[116]Open in a new tab
Effects of AGE-treated EVs-MSC on angiogenic capacity of HUVECs. AGEs,
advanced glycation end products; EVs, extracellular vesicles; HUVEC,
human umbilical vein endothelial cells; MSC, mesenchymal stem cells.
Effects of AGE-Treated EVs-MSC on the Expression of Glucose Transporters and
Metabolic Enzymes in HUVECs
RT-quantitative polymerase chain reaction and Western blot analyses
revealed that EVs-MSC significantly increased the expression of glucose
transporters GLUT1, GLUT3, GLUT4 ([117]Figure 7a–c), and metabolic
enzyme synthesis of cytochrome c oxidase 2 ([118]Figure 7d) at both
mRNA and protein levels ([119]Figure 7e and f). Conversely,
EVs-MSC/AGEs significantly reduced the expression of these genes,
though their levels remained higher than those in the mock group
([120]Figure 7). These results indicated that EVs-MSC contributed to
enhancing glucose uptake and energy metabolism in cells, supporting
their normal function and health. However, EVs-MSC/AGEs significantly
decreased the expression of these key proteins, weakening the
beneficial effects of EVs-MSC. This reduction may be due to impaired
cellular energy metabolism and mitochondrial function, or decreased
insulin sensitivity and glucose metabolism disorders.
Figure 7.
[121]Figure 7
[122]Open in a new tab
Effects of AGE-treated EVs-MSC on the expression of glucose
transporters and metabolic enzymes in HUVECs. (a–d) mRNA levels of (a)
GLUT1, (b) GLUT3, (c) GLUT4, and (d) SCO2 in HUVECs. (e) Western blot
images showing protein levels of GLUT1, GLUT3, GLUT4, and SCO2 in
HUVECs. (f) Quantification of protein levels of GLUT1, GLUT3, GLUT4,
and SCO2 in HUVECs, normalized to actin. ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P <
0.001, ∗∗∗∗P < 0.0001. AGEs, advanced glycation end products; EVs,
extracellular vesicles; GLUT; glucose transporter type; HUVEC, human
umbilical vein endothelial cells; MSC, mesenchymal stem cells; SCO2,
synthesis of cytochrome c oxidase 2.
Differential miRNA Expression in AGE-Treated EVs-MSC and Potential Functional
Prediction
To elucidate the mechanisms of AGEs environment affecting EVs-MSC, we
performed miRNA sequencing on EVs from both groups. Annotation using
Rfam ([123]https://rfam.org/) indicated that both EV types mainly
contained approximately 60% ribosomal RNA, 2% small nucleolar RNA, with
small nuclear RNA in EVs-MSC/AGEs being twice that in EVs-MSC, and the
proportion of transfer RNA being nearly 1.5 times higher
([124]Figure 8a). Other non-miRNA entities were excluded from the
analysis.
Figure 8.
[125]Figure 8
[126]Open in a new tab
Differential microRNA expression and functional enrichment analysis of
miRNAs in EVs-MSC and EVs-MSC/AGEs. (a) Pie charts of distribution in
different types of RNAs (rRNA, snRNA, snoRNA, and tRNA) in EVs-MSC and
EVs-MSC/AGEs. (b) Venn diagram of differentially expressed miRNAs
between EVs-MSC and EVs-MSC/AGEs. (c) Volcano plot of differentially
expressed miRNAs between EVs-MSC and EVs-MSC/AGEs, highlighting
significantly upregulated (red) and downregulated (blue) miRNAs. (d)
Correlation scatter plot comparing the expression levels of miRNAs in
EVs-MSC and EVs-MSC/AGEs. (e) Bar graph of the number of significantly
upregulated and downregulated miRNAs. (f) Heatmap of differentially
expressed miRNAs between EVs-MSC and EVs-MSC/AGEs. (g) Gene ontology
(GO) enrichment analysis of target genes of differentially expressed
miRNAs, categorized into biological processes, cellular component, and
molecular function. (h) Kyoto Encyclopedia of Genes and Genomes (KEGG)
pathway enrichment analysis of target genes of differentially expressed
miRNAs, highlighting the most significantly enriched pathways. AGEs,
advanced glycation end products; EVs, extracellular vesicles; miRNA;
microRNA; MSC, mesenchymal stem cells; snRNA, small nuclear RNA;
snoRNA, small nucleolar RNA; tRNA, transfer RNA.
Following differential analysis of miRNAs, we conducted clustering
analysis and visualization ([127]Figure 8f). Among the top 10
differentially expressed miRNAs, hsa-miR-223-3p, hsa-miR-126-3p_R-1,
pal-mir-10001-p5_1ss1AT, PC-3p-6123_268, mmu-miR-2137_L-2R-1_1ss16AG,
mmu-miR-2137_L-2_1ss16AG, and hsa-miR-26a-5p were significantly
downregulated; whereas hsa-miR-574-5p, hsa-miR-199a-3p_R-1, and
hsa-miR-125b-5p were significantly upregulated ([128]Figure 8c and d).
The top 10 differential miRNA are shown in [129]Table 3. Annotation
revealed 473 common genes between DSS-Exo and Exo ([130]Figure 8b),
with the number of differential genes at different P-values shown in
[131]Figure 8e. Kyoto Encyclopedia of Genes and Genomes pathway
enrichment analysis revealed significant enrichment in metabolic and
oxidative phosphorylation pathways ([132]Figure 8h), and in protein
binding-related biological functions ([133]Figure 8g).
Table 3.
The top 10 differential miRNA
Index 1 2 3 4 5 6 7 8 9 10
miR_name hsa-miR-223-3p hsa-miR-126-3p_R-1 pal-mir-10001-p5_1ss1AT
PC-3p-6123_268 mmu-miR-2137_L-2R-1_1ss16AG mmu-miR-2137_L-2_1ss16AG
hsa-miR-574-5p hsa-miR-26a-5p hsa-miR-199a-3p_R-1 hsa-miR-125b-5p
miR_seq TGTCAGTTTGTCAAATACCCCA TCGTACCGTGAGTAATAATGC
TGGGCGGGCGGGGCCGGGGG AGTTCTTGTGAGCTTTCTCG CGGCGGGAGCCCCGGGGA
CGGCGGGAGCCCCGGGGAG TGAGTGTGTGTGTGTGAGTGTGT TTCAAGTAATCCAGGATAGGCT
ACAGTAGTCTGCACATTGGTT TCCCTGAGACCCTAACTTGTGA
up/down down down down down down down up down up up
fold_change (EVs_AGES (mean)/EVs (mean) 0.32 0.38 0.16 0.07 0.25 0.24
4.12 0.39 1.92 3.38
Log 2 (fold_change) −1.66 −1.39 −2.63 −3.79 −1.99 −2.04 2.04 −1.34 0.94
1.76
P value (t_test) 3.05E-06 3.34E-06 7.75E-06 8.53E-06 9.82E-06 1.61E-05
2.08E-05 2.22E-05 2.25E-05 2.65E-05
EVs (mean) 15,299 12,028 6299 224 12,338 38,966 1255 59,142 13,027 2716
EVs_AGES (mean) 4829 4602 1020 16 3109 9445 5172 23,349 24,959 9176
EVs_AGES/EVs_AGES_1 (norm) 5050 4391 1061 11 2985 8866 5334 24,804
24,987 9425
EVs_AGES/EVs_AGES_2 (norm) 4944 4556 859 16 2779 8420 4963 23,769
24,303 8988
EVs_AGES/EVs_AGES_3 (norm) 4494 4860 1139 22 3561 11,049 5218 21,474
25,586 9115
EVs/EVs_1 (norm) 15,354 12,221 6528 221 12,148 40,445 1109 61,319
13,444 2583
EVs/EVs_2 (norm) 15,614 12,009 6199 233 12,062 37,446 1281 58,642
12,459 2789
EVs/EVs_3 (norm) 14,928 11,853 6169 218 12,803 39,006 1375 57,464
13,178 2775
EVs_AGES/EVs_AGES_1 (raw) 5426 4718 1140 12 3208 9527 5732 26,653
26,849 10,128
EVs_AGES/EVs_AGES_2 (raw) 7158 6596 1243 23 4024 12,192 7185 34,414
35,187 13,014
EVs_AGES/EVs_AGES_3 (raw) 5775 6245 1464 29 4577 14,199 6705 27,596
32,880 11,714
EVs/EVs_1 (raw) 13,526 10,766 5751 195 10,702 35,629 977 54,018 11,843
2276
EVs/EVs_2 (raw) 9083 6986 3606 136 7017 21,784 745 34,114 7248 1623
EVs/EVs_3 (raw) 9252 7346 3823 135 7935 24,174 852 35,614 8167 1720
Expression level high high high middle high high high high high high
[134]Open in a new tab
AGEs, advanced glycation end products; EVs, extracellular vesicles;
miRNA; microRNA.
We further analyzed the metabolic pathways,[135]^32 focusing on
glycolysis, the tricarboxylic acid (TCA) cycle, amino acid metabolism,
lipid metabolism, and nucleotide metabolism. Key steps and metabolites
of glycolysis and the TCA cycle, like glucose, pyruvate, and
acetyl-CoA, exhibited significant changes ([136]Supplementary
Figure S2).
Shown in [137]Supplementary Figure S2, genes marked in green are
enriched by differential miRNAs, playing key roles in oxidative
phosphorylation. Complex I (NADH dehydrogenase) include genes ND1 to
ND6, which initiate NADH oxidation and electron transfer, creating a
proton gradient. Complex II (succinate dehydrogenase) with genes SDHA
to SDHD l links the TCA cycle to the electron transport chain through
succinate oxidation. Complex III (cytochrome bc1 complex) genes Core 1,
Core 2, cytochrome b, and iron-sulfur protein transfer electrons to
cytochrome C and pumping protons. Complex IV (cytochrome c oxidase)
genes COX I to IV transfer electrons to oxygen, forming water; and in
addition, pump protons. Complex V (ATP synthase) subunits use the
proton gradient for ATP production. These genes are critical in the
processes of electron transport and ATP synthesis, illustrating the
crucial role of oxidative phosphorylation in cellular energy
metabolism.
In summary, the AGEs environment influenced the expression of miRNAs in
MSC-derived EVs, regulating the expression of these genes and playing
important roles in cellular energy metabolism and related diseases.
Discussion
This study has shown that MSC-derived EVs obtained from an AGE
environment reduced the positive impact of MSC-derived exosomes on
endothelial cells by altering energy metabolic pathways and inducing
metabolic reprograming to maintain redox balance in HUVEC cells.
Therefore, this study highlighted the potentially overlooked metabolic
and functional deficiencies of these MSCs in clinical applications,
which were like metabolic disorders caused by AGEs in diabetic
complications.
AGEs are a significant etiological factor to contribute to diabetes and
vascular diseases. MSCs and MSC-EVs represent promising therapeutic
approaches for treating diabetic complications, including diabetic foot
and chronic kidney disease.[138]33, [139]34, [140]35, [141]36 However,
many patients with chronic hyperglycemia accumulate substantial amounts
of endogenous and exogenous AGEs in their blood and body tissues, which
affects them during MSC and MSC-EVs treatment.[142]^37^,[143]^38 AGEs
impact not only MSCs but also their EVs. Increasing evidence suggests
that MSCs promote tissue repair through paracrine immunomodulatory and
regenerative factors, with the majority of these factors being
transported by EVs released by MSCs.[144]^28 Previously, we compared
the effects of various inflammatory microenvironments, including
vascular cell adhesion molecule-1, tumor necrosis factor-alpha, and
IL-6, on the miRNA differences in MSC-derived EVs. We found that in
tumor necrosis factor-alpha and IL-6 environments, miRNAs related to
angiogenesis were more downregulated; and the angiogenic ability of
MSCs-exo decreased in the IL-6 environment,[145]^39 indicating that the
microenvironment significantly affects MSCs. In an inflammatory
environment, MSCs induce glycolytic reprograming of
macrophages,[146]40, [147]41, [148]42 and MSCs-exo independently exert
antiinflammatory effects, which has been confirmed in inflammatory
arthritis.[149]^43 MSC-EVs exhibit functions similar to those of their
parent cells, making it essential to understand how disease conditions
(such as AGEs) influence MSC-secreted EVs, because this may affect
their therapeutic effectiveness. We hypothesize that an AGEs
environment may also impair the function and metabolic activities of
MSC-EVs.
This study found that EVs-MSC/AGEs significantly impaired HUVEC
viability, ATP production, and glucose consumption while increasing
lactate production and mitochondrial membrane potential. These findings
indicated a shift toward glycolysis and suggested mitochondrial
dysfunction. The upregulation of glycolysis may serve as a compensatory
mechanism for impaired oxidative phosphorylation. Seahorse XF analysis
showed that HUVECs treated with EVs-MSC/AGEs exhibited lower oxygen
consumption rates across various parameters, indicating reduced
mitochondrial function. Elevated ROS levels and G6PD activity in these
cells suggested that EVs-MSC/AGEs induced oxidative stress, leading to
increased antioxidant responses. This underscored a potential link
between AGEs-induced mitochondrial dysfunction and oxidative stress.
Tube formation assays showed that EVs-MSC/AGEs significantly inhibited
this effect, whereas EVs-MSC enhanced angiogenesis in HUVECs. The
decreased tube formation suggested that AGEs modified the proangiogenic
properties of MSC-derived exosomes, which could influence tissue repair
and regeneration. EVs-MSC increased the expression of glucose
transporters (GLUT1, GLUT3, and GLUT4) and the metabolic enzyme
synthesis of cytochrome c oxidase 2, enhancing glucose uptake and
energy metabolism in HUVECs. In contrast, EVs-MSC/AGEs downregulated
these proteins, impairing glucose metabolism. Overall, the AGEs
microenvironment diminished the beneficial effects of EVs-MSC on
endothelial cells in terms of energy and glucose metabolism.
We conducted high-throughput miRNAs sequencing on both types of
exosomes and found significant differences in miRNA expression between
EVs-MSC and EVs-MSC/AGEs. These miRNAs were related to glycolysis, TCA
metabolism, and oxidative phosphorylation pathways, suggesting that
AGE-treated exosomes may influence cells through miRNA-driven gene
regulation. Enrichment analysis further supported our hypothesis,
aligning with the cellular experiments. Some reports indicated a
vicious cycle between AGEs and oxidative stress: AGEs increased
oxidative stress, and excessive oxidative stress, in turn, accelerates
the production of AGEs, further exacerbating diabetic cardiovascular
complications. AGEs activated signaling cascades that increased ROS
production, increasing oxidative stress by upregulating inducible
nitric oxide synthase and NADPH oxidase, which depleted antioxidants
like glutathione and lower cellular antioxidant capacity.[150]44,
[151]45, [152]46, [153]47, [154]48, [155]49, [156]50
Previous studies showed that in patients with diabetes, the AGE-RAGE
axis promoted endothelial dysfunction and the development of chronic
kidney disease through multiple mechanisms. When AGEs bound to RAGE,
ROS were produced in endothelial cells, which activated the p38 and
extracellular signal-regulated kinase 1/2 signaling pathways, inhibited
the expression of endothelial nitric oxide synthase, and reduced nitric
oxide production.[157]^51 The generation of ROS also induced the
secretion of atherogenic cytokines, such as monocyte chemoattractant
protein-1 and matrix metallopeptidase 9.[158]^52^,[159]^53 Furthermore,
AGEs suppressed of endothelial nitric oxide synthase production,
increased microvascular permeability, and promoted the migration of
macrophages and T cells to the vessel wall, thereby accelerating
inflammation and leading to the formation and instability of
atherosclerotic plaques. In diabetic nephropathy, the AGE/RAGE axis
activated the Rho and β-catenin pathways, leading to the degradation of
vascular endothelial cadherin at endothelial cell junctions, which
exacerbated interendothelial gaps, increased endothelial permeability,
and resulted in microalbuminuria.[160]^54^,[161]^55 In addition, AGEs
increased the concentration of asymmetric dimethylarginine by
activating protein arginine methyltransferase, further inhibiting
nitric oxide production and of endothelial nitric oxide synthase
activity, thereby causing vascular endothelial
dysfunction.[162]^56^,[163]^57 AGEs also promoted mesenchymal
transition and fibrosis by downregulating sirtuin 1 and activating
Smad, which exacerbated renal and vascular damage in diabetic
patients.[164]58, [165]59, [166]60 These studies all indicated that
AGEs had a negative impact on endothelial cell function, including
inhibited proliferation, increased inflammatory responses, and
oxidative stress, primarily involving NADPH oxidase and mitochondria in
oxidative stress. However, there may have been crosstalk between NADPH
oxidase, mitochondria, and glycolysis.[167]^47 Therefore, our findings
further illustrated the real-time impact of AGEs on mitochondrial
energy metabolism and redox state in stem cell–treated vascular
endothelial cells. There was a complex relationship between glycolysis
and oxidative stress. Under high glucose conditions, glycolysis
accelerated, generating pyruvate that entered mitochondria and produced
ATP through the tricarboxylic acid cycle, but also increased
mitochondrial load and ROS production. To alleviate the mitochondrial
burden, cells may have upregulated glycolysis through metabolic
reprograming, thereby reducing ROS production. In addition, glycolytic
byproducts, such as lactate, suppressed NADPH oxidase activity and
reduced oxidative stress. In this process, oxidative stress decreased
the expression of glucose transporters GLUT1 and GLUT4, limiting
glucose uptake and indirectly slowing glycolysis, which helped reduce
mitochondrial load and ROS generation. Glycolysis and oxidative stress
influenced each other: under high glucose or oxidative stress
conditions, cells accelerated glycolysis to reduce mitochondrial ROS
production, whereas oxidative stress also affected glycolysis by
modifying glycolytic enzymes or altering the activity of glucose
transporters.
The results of this study were consistent with existing literature
emphasizing the adverse effects of AGEs on cellular function and
metabolism. The novelty of this research lies in the detailed analysis
of how AGE-treated exosomes mediate these effects in endothelial cells.
Other studies have shown that miRNAs could transfer to mitochondria,
regulating mitochondrial function and metabolic activity. For example,
miR-149 increases mitochondrial function and biogenesis by activating
sirtuin 1 and peroxisome proliferator-activated receptor gamma
coactivator 1. Other miRNAs, such as miR-326,[168]^61 miR-25,[169]^62
miR-338,[170]^63 and miR-181c,[171]^64 directly or indirectly targeted
key enzymes in mitochondrial metabolic pathways, regulating oxidative
phosphorylation and the TCA cycle. MSC-EVs protected cardiac stem cells
from oxidative damage and promote cardiomyocyte regeneration by
transferring miRNAs such as miR-214[172]^65 and miR-21.[173]^66 We
proposed that the AGEs environment affected a complex network of miRNA
regulation because a single miRNA could not fully explain its impact on
endothelial cells. However, these differentially expressed miRNAs point
to specific metabolic signaling pathways, helping us understand how
AGEs influence cell communication and function through exosomes.
Although some studies suggested that MSC-derived exosomes have
potential therapeutic effects, our findings underscored the need to
consider the impact of AGEs and other environmental factors on exosome
function. These results highlighted the potential necessity of
increasing stem cell therapy doses or targeting exosome pathways to
mitigate the adverse effects of AGEs in therapeutic strategies. The
importance of developing exotic-based therapies that can withstand or
counteract these negative influences is particularly crucial in
managing diabetes-related complications. This study has certain
limitations, because it was conducted in vitro, and the results may not
fully replicate in vivo conditions. Future research should validate
these findings in animal models and clinical trials. This study focused
on specific aspects of HUVECs cell function and metabolic pathways.
Comprehensive omics analyses, including proteomics and metabolomics, on
various cell types are needed in the future to gain a broader
understanding of the impact of AGEs.
Conclusion
In conclusion, the AGEs environment diminishes the positive effects of
MSC-derived exosomes on endothelial cells by disrupting energy
metabolic pathways and triggering metabolic reprograming to maintain
the redox balance in HUVEC cells. This suggested that adjustments in
the dosage or frequency of stem cell exosome therapy may be necessary
when treating diabetes and related vascular lesions in clinical
applications. in addition, further research should explore the effects
of AGEs on other cell types and metabolic processes to optimize the
application of stem cell exosomes in various metabolic diseases.
Disclosure
All the authors declared no competing interests.
Acknowledgments