Abstract
Pulmonary veno-occlusive disease (PVOD) is a fatal disease
characterized by the remodelling of pulmonary veins and haemosiderin
accumulation in macrophages. Although (General Control Nonderepressible
2) GCN2 deficiency has been reported in PVOD patients, the underlying
mechanism by which GCN2 deficiency affects the pulmonary venous cells
and the surrounding cells, remains unclear. Here, we perform
immunohistochemistry and scRNA-sequencing analyses to show that
macrophages are the major population affected by GCN2 deficiency and
ferroptosis pathway-related genes are upregulated in lung macrophages
of PVOD patients. Treatment with the specific ferroptosis inhibitor
ferrostatin-1 (Fer-1) reverses the changes in haemodynamic indices
observed in Eif2ak4^K1488X/K1488X hypoxia mice and PVOD model rats.
Furthermore, GCN2 deficiency increases HMOX1 and iron levels to
facilitate ferroptosis in macrophages, and enhances arterial marker
expression in venous endothelial cells (VECs). Specifically, spatial
transcriptome analysis shows increased expression of NRP1, KDR and
EFNB2 through ETS1 in VECs from PVOD patients. Our findings suggest the
potential of targeting macrophage ferroptosis as a therapeutic strategy
for treating related vascular diseases, and of using NRP1/KDR/EFNB2
expression as a specific marker set for venous arterialization.
Subject terms: Diseases, Medical research, Monocytes and macrophages,
Translational immunology, Cell death and immune response
__________________________________________________________________
Pulmonary veno-occlusive disease (PVOD) is a fatal disease
characterised by remodelling of pulmonary veins and haemosiderin
accumulation in macrophages. Here the authors examine the lack of GCN2
in PVOD as this has been observed in human disease and deficiency of
GCN2 in mouse and rat PVOD models alters transcriptome profiles and
increases macrophage ferroptosis.
Introduction
Pulmonary veno-occlusive disease (PVOD) is a heritable autosomal
recessive disease characterized by the remodeling of pulmonary venules,
which leads to pulmonary hypertension (PH)^[42]1–[43]3. PVOD typically
has a poor prognosis, with a mean time from diagnosis to death or need
for lung transplantation of less than 2 years^[44]4,[45]5. Biallelic
EIF2AK4 mutations have been found in all familial PVOD cases and in 9%
of sporadic cases^[46]4,[47]6, with no sex-based differences reported.
However, general control nonderepressible 2 (GCN2) deficiency is not
only caused by biallelic EIF2AK4 mutations, but also has been found in
cancer patients after treatment with alkylating chemotherapeutic
agents, such as cyclophosphamide and mytomycin-C (MMC) or even higher
tobacco exposure^[48]7. Because the mechanism underlying the effects of
GCN2 deficiency on pulmonary venous remodeling is still unclear, lung
transplantation remains the only available therapy for eligible
patients^[49]8. Thus, evidence-based medical therapies for PVOD are
needed^[50]4,[51]9.
GCN2, a serine-threonine kinase that is upregulated in response to
various cellular stresses^[52]10, has been detected in pulmonary vessel
walls and interstitial tissue, mostly in macrophages, in human
lungs^[53]11,[54]12. Compared with gene-corrected isogenic controls,
PVOD-iPSC differentiated endothelial cells (ECs) exhibit excessive
proliferation^[55]13. However, distinguishing changes in heterogeneous
human ECs, including artery, vein, and capillary ECs, can be
challenging^[56]14–[57]16, even though these EC types have distinct
molecular signatures and different physiological functions depending on
their formation and location within the vasculature^[58]14. Moreover,
whether EIF2AK4 mutations play specific roles in the venous endothelial
cells (VECs) subtype fate switch and how the surrounding cells impact
on VECs remain to be clarified.
In the lungs, macrophages are an abundant cell type that critically
regulates normal homeostasis via the secretion of inflammatory factors
and chemokines, which contribute to endothelium permeability and
activation during the progression of PH^[59]17. Since the presence of
hemosiderin-laden macrophages in the lungs is one of the main features
of PVOD, we hypothesize that the EIF2AK4 mutation alters the
endothelium by affecting the iron metabolism of macrophages in the
pulmonary vascular niche.
In this work, we perform single-cell RNA transcriptome sequencing
(scRNA-seq) on lung samples collected from PVOD patients and from
mitomycin-C (MMC)-induced PVOD model rats (MMC rats) to identify the
major affected cell types and regulators involved in PVOD. We identify
arterial markers expressed in remodeled veins surrounded by
hemosiderin-laden macrophages in the lungs of PVOD patients. Since the
lack of an animal genetic model for EIF2AK4 mutation-bearing PVOD is
one reason for the limited understanding of this devastating
disease^[60]18,[61]19, we generate Eif2ak4^K1488X/K1488X mice by
knocking in the human disease-causing mutation and PVOD patient-induced
pluripotent stem cells (iPSCs) to recapitulate the pathogenesis
observed in the lungs of PVOD patients^[62]20. By combining scRNA-seq,
spatial transcriptional sequencing and immunofluorescence staining, we
demonstrate arterialization of the venous endothelium with markedly
elevated NRP1/KDR/EFNB2 expression at vessel lesion sites. These
findings suggest the important role of macrophage ferroptosis in
arterialization of venous endothelium.
Results
Ferroptosis-related gene expression in lung macrophages is increased in PVOD
patients with EIF2AK4^mut
We sought to clarify the role of EIF2AK4 mutation in the pathobiology
of the pulmonary vasculature, especially the key factors that impact
the development of occlusive venous lesion. All patients had pathogenic
characteristics of advanced PVOD with human EIF2AK4 mutation in two
alleles with no sex bias (Fig. [63]1a). We carried out immunoblotting
of GCN2 (the protein encoded by EIF2AK4) in lung tissues obtained from
five control individuals and five patients bearing EIF2AK4 mutations,
which showed absence of GCN2 protein expression in the PVOD patients
(Fig. [64]1b). Consistent with the immunoblotting results,
immunostaining analysis revealed that GCN2 was highly expressed in
macrophages from the lung tissues of control individuals, but not in
PVOD patient lungs (Figs. [65]1c and [66]S1a, b). In agreement with a
previous study^[67]21, we also observed that the number of
hemosiderin-laden macrophages was obviously increased in PVOD patients
(Figs. [68]1d and [69]S1c). The typical pathological features
distinguishing PVOD from other forms of PH include pulmonary hemorrhage
and accumulation of iron-containing hemosiderin deposits.
Fig. 1. Ferroptosis-related gene expression in lung macrophages is increased
in PVOD patients with EIF2AK4^mut.
[70]Fig. 1
[71]Open in a new tab
a DNA sequencing analysis of tissues from pulmonary veno-occlusive
disease (PVOD) patients in this study confirms EIF2AK4 mutations. M:
Male, F: Female. b Western blot showing the expression levels of GCN2
in Control or PVOD patient lung tissues; n = 5 individuals. c
Representative images of MARCO (red) and GCN2 (green)
immunofluorescence and DAPI (blue) staining of lung tissues from
Control and PVOD patients. The data are representative images. White
arrow: macrophages. Scale bar = 20 µm. n = 6 microscope fields from six
individuals with similar results. d Representative images of lung
tissues stained with haematoxylin and eosin (H&E). Red arrow:
macrophages; Black arrow: pulmonary vein. Scale bar = 50 µm. Control,
n = 6 individuals; PVOD n = 9 individuals with similar results. e UMAP
projection showing the main cell type identified by integrated
clustering analysis of scRNA-seq datasets from three Controls and three
EIF2AK4^mut PVOD patients. f Bubble plot showing the incoming and
outgoing interaction strengths for each subpopulation of immune cells
in the Control and PVOD groups. The dot size represents the number of
interactions. g GSEA of differentially expressed genes in alveolar
macrophages, interstitial macrophages, and monocytes between the
Control and PVOD groups. The ferroptosis-associated gene set was
obtained from FerrDb. NES, normalized enrichment score. h Control and
PVOD patient lung tissues were stained with Perls’ DAB to label ferric
iron deposits. Scale bar = 50 µm. Control, n = 7 individuals; PVOD
n = 9 individuals with similar results. i Heme iron levels in the lungs
of Control and PVOD patients were measured. n = 5 individuals. j
Non-heme iron levels in the lung were measured in Controls and PVOD
patients. n = 5 individuals. k The MDA content in the lungs of Control
and PVOD patients was measured. n = 5 individuals. l Representative
images of IHC analysis of 4-HNE content in Control and PVOD patient
lung tissues. Scale bar = 50 µm. The data are presented as the
means ± s.e.m.; unpaired two-sided t test. Each dot represents an
individual biological replicate, at least three independent
experiments. P values are indicated in the figures. Source data are
provided as a [72]Source data file.
Next, we performed single-cell RNA sequencing (scRNA-seq) of explanted
lung tissue samples from three patients with confirmed EIF2AK4^mut PVOD
(obtained after lung transplantation) to define the involved cell types
and their roles in this disease. We obtained high-quality
transcriptomic data from 28,769 single cells after stringent
segregation, and integrated this dataset with data from three control
samples to perform cell type annotation on the basis of a reference
dataset from the Human Lung Cell Atlas (HLCA)^[73]22,[74]23. All the
samples presented similar cell type compositions and proportions
(Figs. [75]1e and [76]S1d–f and [77]S2). To identify the cell
population that was most affected by EIF2AK4^mut, we considered
differences in cell–cell interactions to be potential sources of these
phenotypic differences by comparing ligand-receptor interaction
strengths among all the cell subtypes in the control individuals and
PVOD patients. We found that the overall strength with which
macrophages communicate with other cell types was significantly
increased in PVOD patients (Fig. [78]1f).
Differential gene expression enrichment and pathway scoring analysis of
macrophages, including alveolar macrophages (AMs), interstitial
macrophages (IMs), and monocytes, from controls and PVOD patients
revealed that ferroptosis-associated gene expression was highly
increased in PVOD patients (Figs. [79]1g and [80]S1g). The degree of
iron deposition, as determined by enhanced Perls’ DAB staining,
progressively increased in PVOD patients (Figs. [81]1h and [82]S1h,
[83]i). Iron is required for the accumulation of lipid peroxidation
products to induce ferroptosis^[84]24. We observed substantial lung
iron accumulation (Fig. [85]1i, j) and lipid peroxidation, as evidenced
by increased levels of MDA (Fig. [86]1k) and 4-HNE (Figs. [87]1l and
[88]S1j) expression in PVOD patients. These observations suggest that
ferroptosis was induced in the lung macrophages of PVOD patients with
EIF2AK4^mut.
Eif2ak4^K1488X/K1488X mice as a model for inducing pulmonary venous
remodeling in PVOD
To recapitulate the phenotype of genetic PVOD, we generated a knock-in
mouse strain that bears the same disease-causing mutation (a premature
stop codon) in exon 33 of the endogenous EIF2AK4 locus as PVOD 1 and
his family shown in Figs. [89]1 and [90]2a. Homozygous
Eif2ak4^K1488X/K1488X mice presented normal birth rates, although GCN2
protein expression in the lungs was reduced in these mice
(Fig. [91]2a). At 6 months of age, no detectable alterations in the
total pulmonary vascular resistance index (TPVRI), the right
ventricular systolic pressure (RVSP) and the extent of RVH were
observed in Eif2ak4^K1488X/K1488X mice compared with wild-type (WT)
mice (Fig. [92]2b–d). To induce a severe pulmonary vascular phenotype,
we introduced hypoxia as a trigger for capillary contraction and
endothelium leakage. After 6 weeks of hypoxia exposure, the TPVRI and
RVSP values were significantly greater in the Eif2ak4^K1488X/K1488X
mice than in the WT mice (Fig. [93]2b, c). Reduced cardiac output (CO)
was found in these Eif2ak4^K1488X/K1488X mice (Fig. [94]S4b), but the
extent of RVH was not significantly different between the two groups,
even analyzed with different sex (Fig. [95]2d).
Fig. 2. Eif2ak4^K1488X/K1488X mice as a model for inducing pulmonary venous
remodeling in PVOD.
[96]Fig. 2
[97]Open in a new tab
a DNA sequencing analysis of Eif2ak4^K1488X/K1488X mice confirming the
EIF2AK4 mutation. Western blot revealing decreased expression of GCN2
in Eif2ak4^K1488X/K1488X mouse lung tissues (n = 3 mice/group). b–d
Wild-type (WT) and Eif2ak4^K1488X/K1488X (K1488X) mice were subjected
to normoxia or hypoxia for 6 weeks the total pulmonary vascular
resistance index (TPVRI) value, right ventricular systolic pressure
(RVSP) and right ventricular hypertrophy (RVH) in the model mice (b
male:n = 4 mice/group, female: n = 4 mice/group; c, d male:n = 5
mice/group; female: n = 5 mice/group). TPVRI: Normoxia K1488X vs
Hypoxia K1488X, p = 3.5 × 10^−9; Hypoxia WT vs K1488X, p = 7 × 10^−7.
RVSP: Normoxia K1488X vs Hypoxia K1488X, p = 2 × 10^−8; Normoxia WT vs
Hypoxia WT, p = 4.6 × 10^−7. RVH: Normoxia K1488X vs Hypoxia K1488X,
p = 7 × 10^−8; Normoxia WT vs Hypoxia WT, p = 5 × 10^−8. e
Representative images of H&E-stained samples from the model mice. Scale
bar = 100 µm. f Representative images of α-SMA (cyan), CD31(red), NR2F2
(yellow) and DAPI (blue) immunofluorescence staining of veins (with
NR2F2 and DAPI co-staining), arteries and microwessels from WT and
Eif2ak4^K1488X/K1488X mice under nomaxia and hypoxia. White scale
bar = 50 µm. Yellow scale bar = 20 µm. White arrow: vessel. g Percent
wall thickness of pulmonary arteries (n = 15 vessels of 7 mice/group),
medial thickness of pulmonary veins (n = 15 vessels of 7 mice/group),
and muscularization (%) of microvessels (n = 5 mice/group) in the model
mice. Arteries: Normoxia K1488X vs Hypoxia K1488X, p = 6 × 10^−8;
Normoxia WT vs Hypoxia WT, p = 2 × 10^−9. Veins: Normoxia K1488X vs
Hypoxia K1488X, p = 6 × 10^−9; Normoxia WT vs K1488X, p = 1 × 10^−6;
Hypoxia WT vs K1488X, p = 1 × 10^−12. Microvessels: Non WT vs Hypoxia
WT, p = 9 × 10^−11; Full WT vs Hypoxia WT, p = 1 × 10^−6. h Non-heme
iron levels in the lungs of the mice were measured. n = 7 mice/group. i
Heme iron levels in the lungs of the mice were measured. n = 7
mice/group. Normoxia K1488X vs Hypoxia K1488X, p = 2.9 × 10^−5;
Normoxia WT vs Hypoxia WT, p = 1.1 × 10^−5. j Ferric iron deposits in
the model mice were stained with Perls’ DAB. Scale bar = 50 µm. k MDA
content in the lungs of the mice was measured. Normoxia WT vs K1488X,
p = 5 × 10^−5. l Representative images of 4-HNE staining in mice. Scale
bar = 50 µm. The data are presented as the means ± s.e.m.; two-way
ANOVA with Tukey’s multiple comparison test. Each dot represents an
individual biological replicate, at least three independent
experiments. P values are indicated in the figures. Source data are
provided as a [98]Source data file.
Histopathological analysis revealed the substantial infiltration of
inflammatory cells around the pulmonary vein in Eif2ak4^K1488X/K1488X
mice under hypoxia (Fig. [99]2e). Morphological analysis of vessels via
immunofluorescent staining revealed wall thickening within the
pulmonary arterioles in WT and Eif2ak4^K1488X/K1488X mice under
hypoxia; strikingly, the muscularization of venules surrounded by
inflammatory cells, indicating venous remodeling, was specifically
detected in Eif2ak4^K1488X/K1488X mice with or without hypoxia
(Figs. [100]2f, g and [101]S4g). We found irreversible PVOD phenotype
in Eif2ak4^K1488X/ K1488X mice compared with WT after reoxgenation
(Fig. [102]S3). Furthermore, GCN2-deficient bone marrow transplanted
(BMT) mice had significantly elevated TPVRI, RVSP and worse right heart
function than WT BMT mice under hypoxia (Fig. [103]S5).
We also detected significantly increased iron levels in
whole-mouse-lung homogenates from Eif2ak4K^1488X/K1488X mice under
hypoxia (Fig. [104]2h). Interestingly, heme-iron levels were
significantly increased in hypoxic mice, but did not elevated in
Eif2ak4K^1488X/K1488X mice compared with control mice under hypoxia
(Fig. [105]2i). Consistent with the heme iron levels, we found no
significant difference in endothelium permeability between WT and
Eif2ak4K^1488X/K1488X mice under hypoxia (Fig. [106]S4c). This finding
suggested that blood cells that leak through the endothelium are not
the source of the elevated iron observed in mutant mouse lungs, another
possibility could be that iron recycling is defective in mutant
macrophages, leading to iron accumulation. Moreover, Perls’ DAB
staining revealed that macrophages in the lungs of
Eif2ak4K^1488X/K1488X mice presented greater levels of iron deposition
than those in the lungs of WT mice under hypoxia (Figs. [107]2j and
[108]S4d). To confirm the occurrence of macrophage ferroptosis, we then
measured lipid peroxidation in the lung tissue. Significantly elevated
MDA levels (Fig. [109]2k) and enhanced 4-HNE staining of macrophages
(Figs. [110]2l and [111]S4e) were also observed in the lungs of
Eif2ak4K^1488X/K1488X mice under hypoxia. Moreover, we examined iron
accumulation in other organs, including the kidney, liver, spleen and
heart. Increased iron deposition was detected in the liver and spleen
but not in the kidney or heart (Fig. [112]S4f). Taken together, these
findings suggest that macrophages bearing the Eif2ak4 mutation were
refractory to iron recycling, which contributed to pulmonary venous
remodeling in the mice.
Fer-1 reverses PVOD in Eif2ak4^K1488X/K1488X hypoxia-induced mice and MMC
rats
To confirm the importance of macrophage ferroptosis in PVOD
development, we examined the effects of the ferroptosis inhibitor
ferrostatin-1 (Fer-1) in the established PVOD mouse model.
Eif2ak4^K1488X/K1488X mice were reared under hypoxic or normoxic
conditions for 6 weeks and treated with vehicle or Fer-1 either from
the beginning of the hypoxia period (prevention protocol) or beginning
on day 21 of hypoxia exposure (reversal protocol) (Fig. [113]3a). We
observed that Fer-1 treatment significantly reduced the TPVRI, RVSP and
RVH in mice treated with both protocols, even analyzed with different
sex (Fig. [114]3b). Fer-1 reversed the histopathological phenotype of
PVOD, including reductions in the venous wall thickness and
inflammatory cells infiltration (Figs. [115]3c and [116]S4h).
Morphometric analysis and quantification of α-SMA staining revealed
reduced thickening of the pulmonary artery and venous wall and
muscularization of microvessels in the mice subjected to both protocols
(Fig. [117]3d, e). Whereas Fer-1 cannot reverse PH in hypoxic WT mice
(Fig. [118]S7). Together, these findings confirmed that ferroptosis
inhibition reversed the PVOD phenotype in Eif2ak4^K1488X/K1488X hypoxia
mice.
Fig. 3. Fer-1 reverses PVOD in Eif2ak4^K1488X/K1488X hypoxia-induced mice and
MMC rats.
[119]Fig. 3
[120]Open in a new tab
a Schematic diagram of the experimental design. Eif2ak4^K1488X/K1488X
mice (K1488X) were subjected to hypoxic or normoxic conditions for 42
days and treated with vehicle or Ferrostatin-1 (Fer-1) from the start
of the hypoxia treatment (prevention protocol) or beginning at 21 days
(reversal protocol). b Assessment of TPVRI, RVSP and RVH in the mice
(TPVRI male:n = 4,4,4,3 mice/group, female: n = 3,3,3,4 mice/group;
RVSP male:n = 4,3,4,3 mice/group, female: n = 3,4,3,4 mice/group; RVH
male:n = 4,4,4,3 mice/group, female: n = 3,3,3,4 mice/group). TPVRI:
K1488X vs Hypoxia, p = 3.9 × 10^−9; Hypoxia vs Prevention,
p = 1.8 × 10^−5; Hypoxia vs Reversal, p = 2 × 10^−5. RVSP: K1488X vs
Hypoxia, p = 6 × 10^−8; Hypoxia vs Prevention, p = 9 × 10^−6; Hypoxia
vs Reversal, p = 2 × 10^−5. RVH: K1488X vs Hypoxia, p = 9.7 × 10^−7. c
Representative images of H&E-stained lung sections from the mice
described in a. Pulmonary veins (arrows), scale bar = 100 µm. The
experiment was repeated independently five times with similar results.
d Representative images of α-SMA staining in lung sections from the
mice described in (a). Scale bar = 50 µm. e Percent wall thickness of
pulmonary arteries (n = 15 vessels of 7 mice /group), medial thickness
of pulmonary veins (n = 15 vessels of 7 mice/group), and
muscularization (%) of microvessels (n = 6 mice/group) in the mice
described in a. Arteries: K1488X vs Hypoxia, p = 5.8 × 10^−7. Veins:
K1488X vs Hypoxia, p = 7.5 × 10^−12; Hypoxia vs Prevention,
p = 1 × 10^−10; Hypoxia vs Reversal, p = 1.7 × 10^−9. Microvessels: Non
K1488X vs Hypoxia, p = 2 × 10^−11; Hypoxia vs Prevention,
p = 2 × 10^−7; Hypoxia vs Reversal, p = 3.9 × 10^−5. Full K1488X vs
Hypoxia, p = 2 × 10^−11; Hypoxia vs Reversal, p = 9 × 10^−10. f
Schematic diagram of the experimental design. The rats were given
3 mg/kg mitomycin-C (MMC) (once per week for 2 weeks, i.p.) or vehicle
for 35 days and Fer-1 or saline from the start of the MMC treatment
(prevention protocol) or beginning at 21 days (reversal protocol). g
Assessment of TPVRI, RVSP and RVH in the rats (n = 7 rats/group)
described in f. TPVRI: Control vs MMC, p = 5.9 × 10^−6; RVSP: Control
vs MMC, p = 4 × 10^−7; RVH: Control vs MMC, p = 5 × 10^−5. h
Representative images of H&E-stained lung sections from the rats
described in (f). Pulmonary veins (arrows), scale bar = 100 µm. The
experiment was repeated independently five times with similar results.
i Representative images of α-SMA staining in the pulmonary arteries,
veins and microvessels of the rats described in (f). Scale bar = 50 µm.
j Surface open lumen/total area (%) of pulmonary arteries and veins
(n = 15 vessels of 5 rats/group) and muscularization (%) of
microvessels (n = 6 rats/group) in the rats described in (f). Arteries:
Control vs MMC, p = 7 × 10^−12; MMC vs Prevention, p = 4 × 10^−9; MMC
vs Reversal, p = 1 × 10^−5. Veins: Control vs MMC, p = 8 × 10^−12; MMC
vs Prevention, p = 2 × 10^−5; MMC vs Reversal, p = 1 × 10^−6.
Microvessels: Non Control vs MMC, p < 1 × 10^−15; Mild MMC vs Reversal,
p = 9.6 × 10^−9; Moderate Control vs MMC, p < 1 × 10^−15, MMC vs
Reversal, p = 6 × 10^−5; Severe Control vs MMC, p = 5.7 × 10^−7. The
data are presented as the means ± s.e.m.; one-way ANOVA with Tukey’s
multiple comparison test. Each dot represents an individual biological
replicate, at least three independent experiments. P values are
indicated in the figures. Source data are provided as a [121]Source
data file.
To investigate whether macrophage ferroptosis, which was observed in
the genetic form of PVOD, also occurs in sporadic PVOD. We performed
scRNA-seq on whole lung tissues from control rats and MMC-treated rats
(female, which are more sensitive to MMC treatment^[122]25), a
non-genetic model of disease in which reduction of GCN2 expression is a
central feature (Fig. [123]S8a, b). These MMC rats exhibited typical
phenotypes of PVOD, including reduced pulmonary artery and venous lumen
areas and capillary hematomas (Fig. [124]S8e). A total of 24,156 cells
from 4 samples (from 2 control rats and 2 MMC rats) were included after
quality control (Fig. [125]S9). Combined Seurat analysis provided a
detailed classification of immune cells (Fig. [126]S9c). Enrichment
scores for iron accumulation signatures (IAS)^[127]26 and ferroptosis
gene sets^[128]27 were calculated, revealing a significant elevation in
macrophages, within the MMC group (Fig. [129]S8c, d). Iron levels in
whole-lung homogenates were significantly increased in MMC rats
(Fig. [130]S8f, g). Macrophages had greater levels of iron deposition
in the MMC than in control rat lungs (Fig. [131]S8h, i). Significantly
elevated lipid peroxidation were also observed in the MMC rats
(Fig. [132]S8j–l). Overall, consistent with our observations showed
above, ferroptotic macrophages and accumulated iron in the interstitium
may induce the PVOD phenotype in MMC rats.
We examined the effects of Fer-1 in MMC rats^[133]28. The rats were
given 3 mg/kg MMC (once per week for 2 weeks, i.p.) for 5 weeks, with
or without Fer-1 administered either from the beginning of MMC
treatment (prevention protocol) or starting on day 21 of MMC treatment
(reversal protocol) (Fig. [134]3f). Fer-1 reduced the TPVRI, RVSP and
ameliorated RVH in rats treated with both prevention and reversal
protocols (Fig. [135]3g). Similarly, Fer-1 prevented or rescued the
histopathological phenotype of PVOD, reversing the pulmonary artery and
venous lumen areas and the incidence of capillary hematomas, in the
treatment groups (Fig. [136]3h). Morphometric analysis revealed reduced
initial narrowing within pulmonary arteries and veins, and
quantification of α-SMA staining indicated alleviation of the
muscularization microvessels in rats treated with both prevention and
reversal protocols (Fig. [137]3i, j).
GCN2 deficiency enhances HMOX1 expression and promotes ferroptosis in
macrophages
To identify the downstream mediator of GCN2, we performed
differentially expressed genes (DEGs) analysis of scRNA-seq data from
macrophages and determined that HMOX1 was among the top DEGs
(Fig. [138]4a). The protein encoded by HMOX1, heme oxygenase 1 (HMOX1),
catalyzes the rate-limiting step in heme degradation to release iron,
and an aberrant elevation in HMOX1 levels may initiate ferroptosis
under pathological conditions^[139]29. We performed Western blot
analysis of HMOX1 and the ferroptosis markers FTL, FTH, and TFRC in all
the PVOD patient lung tissue samples and observed significantly
elevated protein expression compared with that in the control samples
(Fig. [140]4b, c). The expression of all of these factors was
significantly increased in whole-lung tissue homogenates from MMC rats
(Fig. [141]4e, f) and Eif2ak4^K1488X/K1488X hypoxia mice (Fig. [142]4h,
i) and in Eif2ak4^K1488X/K1488X bone marrow-derived macrophages (BMDMs)
(Fig. [143]4j, k). Increased HMOX1 expression was also confirmed in
GCN2 knockout HT1080 cells in the presence of additional iron
(Fig. [144]S10a, b). Furthermore, the immunofluorescence results
confirmed that HMOX1 was highly expressed in macrophages from PVOD
patients and MMC rats (Fig. [145]4d, g).
Fig. 4. GCN2 deficiency enhances HMOX1 expression and promotes ferroptosis in
macrophages.
[146]Fig. 4
[147]Open in a new tab
a Volcano plot depicting the differentially expressed genes in alveolar
macrophages from PVOD patients and Controls. The violin plot highlights
HMOX1 expression, identified as significantly different. P values were
determined via two-sided Wilcoxon rank-sum test with Bonferroni
correction for multiple testing. p = 1.42e-686. b, c Western blot and
quantification of HMOX1, FTH, FTL, and TFRC in Control and PVOD lung
tissues. Data are presented as the means ± s.e.m. (n = 5 individuals);
unpaired two-sided t test. d Representative images and quantification
of MARCO(red) and HMOX1(green) immunofluorescence and DAPI (blue)
staining of lung tissues from Control and PVOD patients. Scale
bar = 20 µm. Data are presented as the means ± s.e.m. (n = 6
individuals); unpaired two-sided t test. HMOX1, p = 3.5 × 10^−5. e, f
Western blot of HMOX1, FTH, FTL, and TFRC in Control and MMC rat lungs.
Data are presented as the means ± s.e.m. (n = 5 rats/group); unpaired
two-sided t test. FTH, p = 8.39 × 10^−5. g Representative images and
quantification of MARCO(red) and HMOX1(green) immunofluorescence and
DAPI (blue) staining of lung tissues from Control and MMC rats. Scale
bar = 20 µm. Data are presented as the means ± s.e.m. (n = 5
rats/group); unpaired two-sided t test. h, i WT and
Eif2ak4^K1488X/K1488X mice were subjected to hypoxia for 6 weeks.
Western blot of HMOX1, FTH, FTL, and TFRC in mouse lungs. Data are
presented as the means ± s.e.m. (n = 7 mice/group); two-way ANOVA with
Tukey’s multiple comparison test. HMOX1, Hypoxia WT vs K1488X,
p = 1.7 × 10^−5; Normoxia K1488X vs Hypoxia K1488X, p = 2.3 × 10^−6. j,
k Western blot of HMOX1, FTH, FTL and TFRC in WT or
Eif2ak4^K1488X/K1488X BMDMs treated with (FAC) or without (Control)
300 µM FAC for 48 h. Data are presented as the means ± s.e.m. (n = 7
mice/group); two-way ANOVA with Tukey’s multiple comparison test.
HMOX1, K1488X Control (Con) vs FAC, p = 5 × 10^−6; FTH, WT Con vs FAC,
p = 2 × 10^−9, K1488X Con vs FAC, p = 9.8 × 10^−12; FTL, WT Con vs FAC,
p = 9.7 × 10^−11, K1488X Con vs FAC, p = 5 × 10^−11; TFRC, WT Con vs
FAC, p = 2 × 10^−6, K1488X Con vs FAC, p = 2.7 × 10^−6. l Cell
viability was measured in WT and Eif2ak4^K1488X/K1488X BMDMs treated
with the indicated concentrations of FAC for 48 h and in normal control
(NC) and GCN2^−/− (gRNA) HT1080 cells treated with the indicated
concentrations of FAC for 48 h. Data are presented as the
means ± s.e.m. (n = 6 replicates); unpaired two-sided t tests. BMDM,
FAC 300 µM, p = 1.3 × 10^−6, FAC 500 µM, p = 8.3 × 10^−5; HT1080, FAC
100 µM, p = 3 × 10^−5, FAC 200 µM, p = 1.1 × 10^−5. m Lipid
peroxidation in BMDMs treated with FAC for 12 h, assayed using BODIPY
581/591 dye. Representative microscopy images are shown. Scale
bar = 50 µm. The data are presented as the means ± s.e.m. (n = 15
microscope fields from 5 mice); two-way ANOVA with Tukey’s multiple
comparison test. WT Con vs FAC, p = 9 × 10^−8, K1488X Con vs FAC,
p = 1 × 10^−12, FAC WT vs K1488X, p = 1 × 10^−8. Each dot represents an
individual biological replicate, at least three independent
experiments. P values are indicated in the figures. Source data are
provided as a [148]Source data file.
These findings suggest that GCN2 deficiency renders macrophages more
susceptible to ferroptosis. To investigate this hypothesis, we
evaluated the effects of the ferroptosis activators ferric citrate
(FAC) in BMDMs obtained from WT and Eif2ak4^K1488X/K1488X mice.
Furthermore, we generated EIF2AK4 knockout HT1080 cells (a cell line
sensitive to ferroptosis) via CRISPR/Cas9 targeted editing to examine
the effects of ferroptosis activation in these cells and in control
cells. Treatment with FAC reduced cell viability in a dose-dependent
manner in all the cells examined, and this ferroptosis-activating
effect was stronger in the mutant cells than in the normal control
cells (Fig. [149]4l). BODIPY 581/591 staining revealed greater lipid
peroxidation in response to FAC exposure in Eif2ak4^K1488X/K1488X BMDMs
than in WT BMDMs (Fig. [150]4m). Moreover, we observed a significant
increase in intracellular iron deposition in GCN2-deficient BMDMs and
HT1080 cells following iron treatment (Fig. [151]S10c–f). However, the
GSH/GSSG ratio, an indicator of redox status, did not significantly
change in human lung tissue or iron-treated cells (Fig. [152]S10g, h).
Also, the expression of other ferroptosis-related factors, including
ACSL4, TXNRD1, and GPX4 were not significantly changed, which excluded
the possibility of the involvement of these factors (Fig. [153]S11).
These findings suggested that GCN2 deficiency sensitized macrophages to
ferroptosis induction via increased HMOX1 expression, especially under
iron stimulation.
Previous studies have shown that GCN2 deficiency leads to recruitment
of the transcription factor NRF2 to the HMOX1 gene, resulting in
elevated HMOX1 expression^[154]30,[155]31. Therefore, we analyzed the
expression of NRF2 in BMDMs and HT1080 cells by immunoblotting.
Consistent with previous findings, GCN2-deficient cells presented a
significant increase in NRF2 expression under iron stimulation
(Fig. [156]S12a–d). To examine whether HMOX1 could exaggerate the
phenotype in our model mice, we challenged Eif2ak4^K1488X/K1488X mice
with the HMOX1 activator hemin. The stimulation of
Eif2ak4^K1488X/K1488X mice with hemin developed PH phenotypes within 6
weeks (Fig. [157]S12e). However, the treatment of PVOD model mice and
model rats with either an HMOX1 activator, hemin, or an HMOX1
inhibitor, Znpp, did not significantly promote or inhibit PVOD
progression (Fig. [158]S12f, g). Collectively, these findings indicate
that elevated levels of HMOX1/FTL/FTH increase the susceptibility of
GCN2-deficient macrophages to ferroptosis, but targeting HMOX1 alone is
not desirable for the treatment of PVOD.
GCN2 deficiency enhances VEC arterialization and smooth muscle cell
recruitment in the presence of iron
To investigate the effects of macrophages on the pulmonary vasculature,
we next examined the DEGs in EIF2AK4^mut VECs in the lungs of PVOD
patients. ScRNA-seq revealed that genes related to arterial development
(NRP1, KDR, and EFNB2), the arterial specification-related genes NOTCH4
and JAG2, and the secretory marker CXCL12 were highly upregulated in
PVOD VECs compared with control VECs, whereas the venous-related genes
TEK, ACKR1, and ENG presented reduced expression (Fig. [159]5a). When
we specifically extracted the VECs subpopulation for pseudotime
trajectory analysis, we found that VECs from PVOD patients were
predominantly distributed in the high pseudotime regions
(Fig. [160]S2d, e). This finding supports our hypothesis regarding
venous fate transition in PVOD pathogenesis, providing further evidence
for the venous-to-arterial remodeling process at the single-cell level.
These finding suggest that venous arterialization may occur in the
lungs of PVOD patients. Venous arterialization occurs naturally during
certain developmental processes, such as the initial derivation of
coronary arteries from venous VECs in mice. EFNB2 (Ephrin-B2) signaling
contributes to arterial specification via KDR activity^[161]32.
Moreover, NRP1 serves as a co-receptor for VEGF-A and plays a pivotal
role in arteriogenesis by facilitating KDR endocytosis and
trafficking^[162]33. We employed the CRISPR/Cas9 system to knock in the
mutated EIF2AK4 gene (GCN2^−/−) in human umbilical vein ECs (hUVECs);
the high efficiency of this process was confirmed (Fig. [163]S13a).
Treatment of GCN2^−/− hUVECs with macrophage-conditioned medium led to
the upregulation of arterialization-related genes (Fig. [164]S13b).
Fig. 5. GCN2 deficiency enhances arterial markers expression in VECs and
smooth muscle cell recruitment in the presence of iron.
[165]Fig. 5
[166]Open in a new tab
a Violin plots highlighting the differentially expressed genes
associated with arterial and venous identity in venous endothelial
cells from human scRNA-seq data. P values were determined via two-sided
Wilcoxon rank-sum test and marked on each panel. b Western blot of
NRP1, EFNB2, p-ERK in NC or GCN2^−/− (gRNA) hUVECs treated
with (FAC) or without (Control) 660 µM FAC for 72 h. Data are presented
as the means ± s.e.m. (n = 4 replicates); two-way ANOVA with Tukey’s
multiple comparison test. NRP1, NC Control (Con) vs gRNA FAC,
p = 2 × 10^−6. c Schematic of the Transwell coculture model. NC or
GCN2^−/− hUVECs were seeded in the bottom compartment and treated
with/without 660 µM FAC for 72 h, with SMCs seeded on top for 24 h. An
8-µm pore membrane facilitates migration; a 0.4-µm membrane tests
proliferation. d Images and quantification of DAPI-stained SMCs
cocultured with NC or GCN2^−/− (gRNA) hUVECs in an 8-μm pore size
chamber in FAC-treated medium, indicating the migration ability of
SMCs. Scale bar = 100 µm. Data are presented as the means ± s.e.m.
(n = 15 microscope fields from three independent experiments); two-way
ANOVA with Tukey’s multiple comparison test. Con NC vs Con gRNA,
p = 3 × 10^−10, gRNA Con vs FAC, p = 1 × 10^−5. e Images and
quantification of DAPI-stained SMCs cocultured with NC or GCN2^−/−
hUVECs in a 0.4-μm pore size chamber in FAC-treated medium, revealing
the proliferative ability of the SMCs. Scale bar = 100 µm. The data are
presented as the means;± s.e.m. (n = 15 microscope fields from three
independent experiments); two-way ANOVA with Tukey’s multiple
comparison test. NC Con vs FAC, p = 5 × 10^−5, gRNA Con vs FAC,
p = 6 × 10^−8. f Ratio of EdU-positive SMCs after treatment ± 660 µM
FAC for 24 h. Data are presented as the means ± s.e.m. (n = 6
replicates); unpaired two-sided t test. g Representative images of
hUVECs (green) cocultured with SMCs (PKH26, red) for 4 days. Scale
bar = 100 µm. Quantification of total network area, total cord length,
and branch points. Data are presented as the means ± s.e.m. (n = 8
microscope fields from four independent experiments); two-way ANOVA
with Tukey’s multiple comparison test. Number of nodes, NC FAC vs gRNA
FAC, p = 2 × 10^−5, gRNA Con vs FAC, p = 2 × 10^−6; Number of
junctions, gRNA Con vs FAC, p = 4.5 × 10^−5; Total length, gRNA Con vs
FAC, p = 8 × 10^−8; Total branching length, gRNA Con vs FAC,
p = 3 × 10^−7. Each dot represents an individual biological replicate,
at least three independent experiments. P values are indicated in the
figures. Source data are provided as a [167]Source data file.
Screening for secretory factors in human lung macrophages via scRNA-seq
revealed that GDF15, TNF and CCL3 were highly expressed
(Fig. [168]S13c, d). The elevated expression of GDF15, TNF, and CCL3
was validated by ELISA of homogenized human lung tissue and
supernatants collected from iron-treated Eif2ak4^K1488X/K1488X BMDMs
(Fig. [169]S13e). However, the treatment of GCN2^−/− hUVECs with these
factors did not induce arterialization (Fig. [170]S13f). In addition to
the high levels of inflammatory factors in ferroptotic macrophage
supernatants, iron can induce fibrosis in vascular disease, as recently
reported^[171]26,[172]34. In this study, we detected increased
expression of arterialization-related genes in iron-treated GCN2^−/−
hUVECs (Fig. [173]5b and Fig. [174]S14). To examine the effect of iron
on the vasculature, we conducted a Transwell study of human pulmonary
smooth muscle cells (SMCs) with GCN2^−/− hUVECs plated at the bottom
well of the Transwell plate and observed an increase in SMCs migration
(Fig. [175]5c, d). FAC treatment on hUVECs further increased the
proliferation of SMCs (Fig. [176]5c, e), which was not affected by the
addition of iron to the culture medium (Fig. [177]5f). Furthermore, we
established a 3D hUVECs–SMCs coculture assay to confirm the effect of
iron on endothelial network formation (Fig. [178]5g). Compared with the
control culture conditions, GCN2^−/− hUVEC cocultures resulted an
increase in the numbers of SMCs that wrapping around the ECs to provide
physical support and for tube formation. Compared with control
cultures, FAC-treated GCN2^−/− hUVEC cocultures presented increases in
the total endothelial network area, total cord length and number of
branch points. We also examined human pulmonary artery ECs (hPAECs) or
human pulmonary microvascular ECs (hPMECs) treated with iron. There
were no significant changes in gene expression in the hPAECs
(Fig. [179]S15a–c), whereas GCN2 deficiency in hPMECs resulted in
increased KDR, NOTCH4, and JAG2 expression, as well as the increased
expression of Ki67 and PCNA, which are associated with vascular
malformation (Fig. [180]S15d–f).
To determine the direct effects of iron on the GCN2-deficient pulmonary
vasculature in vivo, we intratracheally administered FAC to
Eif2ak4^K1488X/K1488X mice. HE staining of the lungs revealed the
persistent infiltration of inflammatory cells and deposition of
hemosiderin after 14 days of intrapulmonary iron administration
(Fig. [181]S6a). By day 35, the infiltration of inflammatory cells had
decreased, but significant thickening of the blood vessel walls was
observed. Iron staining of the lung tissue revealed abundant iron
deposition from days 14 to 21, particularly in macrophages. However,
iron deposition gradually decreased after 35 days of iron
administration (Fig. [182]S6b). Notably, the RVSP and the extent of RVH
in the mice significantly increased after 14 days of iron
administration, but did not decrease after 35 days, despite the
decrease in iron deposition (Fig. [183]S6c, d). Although there was no
significant change in the thickness of the medial layer in the
pulmonary arteries on day 35, significantly increased medial thickness
in the pulmonary veins and microvessel muscularization was observed
(Fig. [184]S6e–g). In summary, GCN2 deficiency enhanced arterial marker
gene expression in VECs and iron treatment promoted venous medial
thickening in vitro and in vivo.
Enhanced NRP1/KDR/EFNB2 expression as a marker set of the arterialization of
pulmonary VECs
To investigate the spatial distribution of venous arterialization in
PVOD, we performed 10X Visium spatial transcriptomics on lung tissues
from a PVOD patient and two healthy controls (Fig. [185]6a).
Integration of samples using STAligner^[186]35 followed by Leiden
clustering identified nine distinct clusters that were categorized into
four tissue regions: Alveoli, Bronchi, Vessel, and Unspecified areas
based on marker gene expression and histological features (Fig. [187]6b
and Fig. [188]S16a–e).
Fig. 6. Spatial transcriptomics reveals enhanced venous arterialization and
ETS1-mediated gene regulation in PVOD lung vessels.
[189]Fig. 6
[190]Open in a new tab
a H&E-stained images of 10X Visium spatial transcriptomics sections
from Control (n = 2 individuals) and PVOD (n = 1 individual) lung
tissues. The two control samples represent the upper and lower halves
of the same slide (stitched together). Scale bar = 2 mm. b Spatial
mapping of tissue region clusters (Alveoli, Bronchi, Vessel,
Unspecified) on spatial transcriptomics spots from Control (left) and
PVOD (right) lung samples. c Violin plot showing HMOX1 expression
levels across tissue regions in Control and PVOD lung samples. P values
were determined via two-sided Wilcoxon rank-sum test. d Violin plots
depicting expression of arterial endothelial markers (KDR, CXCL12) and
venous related marker (ACKR1) in vessel regions comparing Control and
PVOD groups. P values were determined via two-sided Wilcoxon rank-sum
test. e Violin plots showing arterial and venous endothelial gene set
scores in vessel regions of Control versus PVOD samples. P values were
determined via two-sided Wilcoxon rank-sum test. f Volcano plot of
differentially expressed genes in vessel regions between PVOD and
Control groups. P values were determined via two-sided Wilcoxon
rank-sum test with Benjamini–Hochberg correction for multiple testing.
Significance thresholds were set at |log2 fold change| > 0.5 and
adjusted p-value < 0.05. The top 5 upregulated and top 5 downregulated
genes are annotated in the plot. GO biological processes (g) and KEGG
pathways (h) significantly enriched (FDR < 0.05) from upregulated genes
in PVOD vessel regions. P values were calculated using the
hypergeometric test with Benjamini–Hochberg correction for multiple
testing. Ten relevant terms associated with pulmonary vascular disease
are shown, ranked by combined score. Dot size represents the percentage
of genes in the gene set, and dot color indicates –log10(FDR). i
Volcano plot of transcription factor activity differences (z-score
normalized AUC scores) between Control and PVOD vessel regions analyzed
by the limma method. j Violin plot showing ETS1 AUC scores in Control
and PVOD vessel regions. k Violin plot of ETS1 expression in venous
endothelial cells from scRNA-seq data comparing Control and PVOD
groups. P values were determined via two-sided Wilcoxon rank-sum test.
l ETS1 transcription factor binding motif (metacluster_183.1) obtained
from the cisTarget motif collection (v10nr_clust). m Spatial
distribution of cell type proportions (EC_arterial, EC_venous,
Macrophages, Muscular cells, Fibroblasts) inferred by RCTD
deconvolution. Color intensity corresponds to the relative abundance of
each cell type, with darker colors indicating higher proportions. n
Heatmaps showing Pearson correlation between RCTD cell type scores and
cell death pathway gene set scores in Alveoli (top) and Vessel (bottom)
region of the PVOD lung sample (*P < 0.05, **P < 0.01, ***P < 0.001). P
values are indicated in the figures. Source data are provided as a
[191]Source data file.
Analysis of the vessel regions revealed significant molecular
alterations in PVOD. HMOX1, a marker of oxidative stress, was markedly
elevated in both alveolar and vessel regions of PVOD samples
(Fig. [192]6c). Arterial endothelial markers including KDR and CXCL12
were significantly upregulated, while venous related marker ACKR1 was
reduced in PVOD vessels compared to Controls vessels (Fig. [193]6d).
Gene set scoring confirmed enhanced arterial characteristics with
increased arterial scores and decreased venous scores in PVOD vessels
(Fig. [194]6e). Differential expression analysis of vessel regions
identified 2129 upregulated and 590 downregulated genes in PVOD
(Fig. [195]6f). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and
Genomes (KEGG) pathway enrichment analysis revealed activation of
muscularization and fibrosis-related pathways, including TGF-β and
Notch signaling (Fig. [196]6g, h). Comparison with published PAH
spatial transcriptomics data^[197]36 showed distinct enrichment
patterns, with PVOD characterized by prominent angiogenesis, Wnt-β
catenin, and Notch signaling (Fig. [198]S16f).
To identify regulatory mechanisms underlying PVOD pathology,
transcription factor activity analysis was performed with
pySCENIC^[199]37 analysis. ETS1 emerged as the most significantly
upregulated transcription factor in PVOD vessels (Fig. [200]6i, j),
consistent with its elevated expression in venous ECs from sc-RNA seq
data (Fig. [201]6k). cisTarget database analysis confirmed that ETS1
regulates NRP1 and KDR through a conserved binding motif
(Fig. [202]6l).
Cell type deconvolution with matched single-cell nuclear RNA sequencing
(snRNA-seq) reference data^[203]38 (Fig. [204]S16g–l) revealed
increased venous EC proportions in PVOD (Fig. [205]6m). Correlation
analysis between cell type scores and cell death pathways showed a
specific association between ferroptosis and macrophages in PVOD
samples (Fig. [206]6n), suggesting cell type-specific iron accumulation
response in macrophages.
In human lung tissue sections, we also performed multiple
immunofluorescence staining for NR2F2 (Veins), CD31 (ECs), and α-SMA
(SMCs) to examine the localization of pulmonary venous endothelium.
Staining for the arterial markers NRP1, EFNB2, and KDR revealed that
these arterial genes were highly expressed on the pulmonary venous
endothelium in PVOD patients (Fig. [207]7a). During vessel formation,
EFNB2 regulates arterial formation by upregulating downstream p-ERK,
leading to the differentiation of ECs towards the arterial
lineage^[208]32,[209]33. After treating GCN2-deficient hUVECs with FAC,
we observed that NRP1 and EFNB2 protein expression was elevated
significantly, accompanied by increased p-ERK activity compared with
untreated groups (Fig. [210]5b). Finally, to confirm the effects of
EIF2AK4 mutation on VEC specification in the context of PVOD, we
generated iPSCs from a PVOD patient with EIF2AK4 mutation and a healthy
donor, differentiated the iPSCs into VECs and confirmed NR2F2 and CD31
expression in both lines after mesoderm induction towards VECs
(Figs. [211]7b, d and [212]S17a). Immunoblotting revealed the elevated
expression of p-ERK, ETS1, NRP1 and EFNB2 in PVOD iPSC-VECs compared
with Control iPSC-VECs (Figs. [213]7c, e, f and [214]S17b). These
findings suggest that VECs are prone to differentiate into arterial
cells in the context of GCN2 deficiency.
Fig. 7. Enhanced NRP1/KDR/EFNB2 expression as a marker set of venous
arterialization of the VECs in PVOD patient lung.
[215]Fig. 7
[216]Open in a new tab
a Representative images of NRP1/KDR/EFNB2 (red), NR2F2 (yellow), CD31
(green), and α-SMA (cyan) immunofluorescence and DAPI (blue) staining
of lung tissues from Control and PVOD patients, with the boxed region
magnified. Scale bar = 50 µm. Enlarged view scale bar = 10 µm. The data
are representative images. Control, n = 7 individuals; PVOD n = 9
individuals with similar results. b qRT-PCR analyzed the expression
levels of representative markers at various stages of VECs
differentiation process. Data are presented as the means ± s.e.m.
(n = 4 replicates); two-way ANOVA with Tukey’s multiple comparison
test. CD31 VEC, p = 6 × 10^−12; NR2F2 VEC, p = 4 × 10^−10. c qRT-PCR
analyzed the differential expression levels of candidate genes in
Control-iPSC VEC (Con) and PVOD-iPSC VEC (PVOD). Data are the
mean ± s.e.m. (n = 6), unpaired two-sided t-test. EFNB2 Con vs PVOD,
p = 4.7 × 10^−4; KDR Con vs PVOD, p = 8 × 10^−6. d Immunofluorescence
analysis of a venous marker (NR2F2) with DAPI counterstaining. Scale
bar = 100 µm. The experiment was repeated independently four times with
similar results. e Western blot showing the expression levels of NRP1,
EFNB2, p-ERK, Total-ERK in Control-iPSC VEC (Con) or PVOD
iPSC-VEC (PVOD). The experiment was repeated independently three times
with similar results. f Immunofluorescence analysis of p-ERK with DAPI
counterstaining in Control-iPSC VEC (Con) or PVOD iPSC-VEC (PVOD).
Scale bar = 50 µm. Data are the mean ± s.e.m. (n = 6 replicates),
unpaired two-sided t-test. Each dot represents an individual biological
replicate, at least three independent experiments. P values are
indicated in the figures. Source data are provided as a [217]Source
data file.
In summary, our findings demonstrated that GCN2 deficiency induces
ferroptosis in lung macrophages through the upregulation of HMOX1,
which releases iron to induce NRP1/KDR/EFNB2 expression through ETS1
transcription activation in VECs. Activated ERK drives venous
arterialization and contributes to PVOD development (Fig. [218]8).
Fig. 8. Schematic summary.
[219]Fig. 8
[220]Open in a new tab
Ferroptosis in lung macrophages with GCN2 deficiency upregulates
HMOX-1, which releases iron to induce NRP1/KDR/EFNB2 expression through
ETS1 transcription activation in VECs. Activated ERK drives venous
arterialization and contributes to related vascular diseases. The image
was drawn by Figdraw, with an authorization ID of SWURR94551.
Discussion
We report here that EIF2AK4 mutation-induced macrophage ferroptosis
contributes to venous arterialization in the pulmonary vasculature and
that the inhibition of ferroptosis can reverse pulmonary venous
remodeling in animal models of PVOD. This work also shows that mice
homozygous for a human disease-causing mutation are susceptible to PVOD
with no sex bias, providing a genetic experimental model for this
disease and clarifying the molecular characteristics of venous
arterialization in human disease.
In this study, we assessed ferroptosis-related gene expression in PVOD
patient and model rat lung tissues via scRNA-seq. These observations
are consistent with hemosiderin accumulation in macrophages, a
pathological characteristic of PVOD^[221]39. ScRNA-seq analyses
revealed that although some upregulation was observed in T cells and NK
cells, the highest baseline expression and the most pronounced
disease-associated increase occurred predominantly in tissue-resident
macrophages. Furthermore, GCN2 was reported to control erythrocyte
clearance and then affect iron recycling in mouse liver macrophages
under stress^[222]30. The failure to regulate heme and iron by Eif2ak4
deficient macrophage results in uncontrolled iron release to pulmonary
interstitium and bone marrow derived cells (such as dendritic and T
cells) infiltration. Increased 4-HNE staining and elevated MDA levels
in the lung tissue of PVOD patients and GCN2-deficient mice suggest
that the high-iron microenvironment caused by GCN2 deficiency
contributes to enhanced lipid peroxidation in the lungs, which may
further promote vascular remodeling. PVOD patients have reduced ability
to transfer oxygen from inhaled air to the bloodstream, so hypoxia is
another critical factor, supporting the study of related phenotypes in
our mouse model.
In vitro and in vivo experiments confirmed increased HOMX1 expression
in Eif2ak4-mutated macrophages^[223]2, and we also demonstrated
upregulation of the transcription factor NRF2 in mutant BMDMs and
HT1080 cells. However, HMOX1 inhibition did not reverse this PVOD
phenotype. Since PVOD patients experience lung hemorrhage, increased
HMOX1 expression may be required for macrophages to clear extravascular
red blood cells^[224]40. However, our results demonstrated that
ferroptosis inhibition not only successfully prevented PVOD
development, but also reversed established disease phenotype in
Eif2ak4^K1488X/K1488X mice and MMC rats, suggesting that macrophage
ferroptosis inhibition could be an effective treatment strategy for the
genetic and nogenetic forms of PVOD.
In this study, we addressed the fate transition from venous lineage to
arterial identity in the context of a human disease with various
techniques, including scRNA-seq and multiplex immunohistochemistry, and
identified NRP1/KDR/EFNB2 as a specific marker set for venous
arterialization, consistent with the results of spatial transcriptomic
sequencing. Additionally, we demonstrated enhanced ERK phosphorylation
in GCN2^−/− hUVECs and PVOD-iPSC VECs via immunoblotting and
immunofluorescence staining, which is in line with the finding that
MAPK activation is triggered by iron treatment^[225]41. It was also
reported that transcription activator ETS1 is the downstream effector
of phosphorylated ERK^[226]42. Our study revealed that activated
NRP1/KDR/EFNB2, a core set of markers, can be used for the diagnosis of
venous arterialization in venous occlusive diseases and vein stenosis,
including predict the outcome and prognosis^[227]43,[228]44.
One limitation of the current study is accumulated immune cell in PVOD
lungs may contribute to the individually reduced propotion of vascular
cell and other cell types. So we sorted CD31^+ cells by magnetic beads
and performed scRNA-seq to obtain transcriptional profiles of pulmonary
ECs. To further address this limitation, we employed spatial
transcriptomics and Single-nuclear transcriptomics to better
distinguish and analyze EC types and their expression profiles, and
provide a more balanced perspective on the cellular landscape of the
affected lung tissue. Another limitation is inadequate comparison
between PVOD and other forms of pulmonary arterial hypertension (PAH).
Although we conducted a comparative analysis using scRNA-seq data from
three idiopathic PAH lung tissue samples alongside our PVOD dataset
(Fig. [229]S18), as well as an additional comparison with published PAH
spatial transcriptomics data (Fig. [230]S16f), our findings revealed
both shared and distinct molecular features. However, a comprehensive
understanding of the unique molecular signatures distinguishing PVOD
from PAH remains to be fully elucidated. Such insights are important
for clarifying the distinct pathophysiology of PVOD and reinforcing its
clinical differentiation from PAH. In future studies, screening for the
relevant disease types using this venous arterialization marker set to
ensure that targeted clinical trials involving ferroptosis inhibition
will be crucial.
Overall, we provide a genetic model to study venous arterialization in
human disease. Our study builds on previous reports by clarifying the
details of the interaction between EIF2AK4 defects and iron metabolic
alterations in the pulmonary vascular niche, suggesting that
NRP1/KDR/EFNB2 could be hallmarks of pathogenic venous arterialization
and that targeting the ferroptosis pathway is worth investigating for
the treatment of PVOD and other related vascular diseases.
Methods
Collection of pulmonary veno-occlusive disease (PVOD) lung tissue
Lung tissue samples from PVOD patients(with no sex bias) were obtained
during lung transplantation procedures after written informed consent
was obtained from all patients. Informed consents were obtained from
all human persons. All procedures were approved by the Institutional
Review Boards (IRBs) of the Second Affiliated Hospital of Zhejiang
University School of Medicine (IRB-2021-588 and IRB-2024-1507) and Wuxi
People’s Hospital NO. (2015)36. The diagnosis of PVOD was confirmed via
exome sequencing, which identified biallelic mutations in the EIF2AK4
gene. The samples included multiple sections of proximal, middle, and
distal lung tissue, each approximately 2 cm in size. Human lung tissues
were obtained from PVOD and unused donor-explanted lungs as controls.
The data are shown in Supplementary Table [231]1.
Single-cell RNA sequencing and analysis
Fresh lung tissues from three PVOD patients (one processed with CD31^+
magnetic bead enrichment) and whole lungs from MMC-treated and control
rats (n = 2 each) were enzymatically dissociated into single-cell
suspensions for single-cell RNA sequencing (scRNA-seq). Additionally, a
frozen lung tissue sample from one PVOD patient was processed for
single-nucleus RNA sequencing (snRNA-seq) to be paired with subsequent
spatial transcriptomic analysis. Following quality control (>90%
viability for cells, >70% intact nuclei for frozen tissue), samples
were processed using 10x Chromium 3′ v3 chemistry and sequenced on
Illumina HiSeq 2000.
Raw data were aligned using Cell Ranger v6.0.0 to GRCh38 (human) or
Rnor 6.0 (rat) reference genomes, with pre-mRNA reference included for
snRNA-seq to capture intronic reads. The entire analysis workflow
combined the use of Seurat (v4.3.0), Scanpy^[232]45 (v1.11.2), and
OmicVerse^[233]46 (v1.7.1). Quality control retained cells/nuclei with
<15% mitochondrial content (< 5% for nuclei) and sample-specific gene
detection thresholds. Doublets were removed using Scrublet^[234]47
(v0.2.3). After normalization and scaling, principal component analysis
was performed on 3000 highly variable genes. Batch effects were
corrected using OmicVerse. single. batch_correction (scVI or Harmony
parameters). Cell types were annotated with assistance from
CellTypist^[235]48 (v1.7.0) using the HLCA^[236]23 reference, followed
by graph-based clustering via the Leiden algorithm. DEGs were
identified using scanpy.tl.rank_genes_groups (Wilcoxon test) with
adjusted p-value < 0.05 and log2 fold change > 0.5.
Gene set enrichment analysis (GSEA) was performed on DEGs between
Control and PVOD groups within each cell type subpopulation.
Single-sample gene set enrichment analysis (ssGSEA) was implemented
using the “escape” package (v2.2.3) for gene set scoring across
individual cells, incorporating ferroptosis gene sets from
FerrDb^[237]27 and the IAS gene set from Maus et al.^[238]26 to assess
iron-related cellular states. Cell–cell communication networks were
inferred using CellChat^[239]49 (v1.6.1) to predict ligand-receptor
interactions among immune and EC populations.
10x Genomics Visium spatial transcriptomics and analysis
Formalin-fixed paraffin-embedded (FFPE) tissue sections (5 μm
thickness) from one PVOD patient and two healthy control lungs were
processed using the Visium Spatial Gene Expression for FFPE Kit (10X
Genomics) following manufacturer’s protocols. Both control samples were
captured on a single chip. Sections were deparaffinized with xylene,
rehydrated through a graded ethanol series, and subjected to H&E
staining for morphological assessment. Following probe hybridization
and ligation-based target enrichment specific to the FFPE workflow,
libraries were sequenced on the Illumina NovaSeq platform. Raw FASTQ
files and histology images were processed using Space Ranger v2.0.0
(10X Genomics) to generate gene-spot matrices aligned to GRCh38.
Spatial data integration across the three samples (control1, control2,
PVOD1) was performed using STAligner^[240]35. Normalized data underwent
principal component analysis, and graph-based clustering was performed
using the Leiden algorithm. Arterial and venous signatures were scored
using scanpy.tl.score_genes. DEGs between control and PVOD groups were
identified using scanpy.tl.rank_genes_groups (Wilcoxon rank-sum test)
with adjusted p-value < 0.05 and log2 fold change > 0.5. Pathway
enrichment analysis was performed using gseapy (v1.1.9) for GO, KEGG,
and Hallmark gene sets.
Transcription factor regulatory network analysis was conducted on
vessel regions using pySCENIC^[241]37 (v0.12.1). Cell type
deconvolution was performed using RCTD^[242]50 (spacexr v2.2.1), with
the paired snRNA-seq data from the same PVOD patient serving as
reference for the PVOD spatial data, and publicly available healthy
lung snRNA-seq data^[243]38 for the control spatial data. For each
spot, cell type proportions were correlated with gene set scores for
four cell death pathways (ferroptosis, apoptosis, necroptosis,
pyroptosis) using Pearson correlation. The predominant cell type per
spot was defined as “maxtype” based on the highest deconvolution score.
MMC-Induced rat model and treatments
All the rat experiments performed in the present study were approved by
the Animal Institutional Review Boards (AIRB) of the Second Affiliated
Hospital of the Zhejiang University School of Medicine (AIRB-2021-967
and AIRB-2024-327). Five-week-old female Wistar rats (150‒200 g) were
randomly assigned to treatment groups. The control rats were given
intraperitoneal injections of a control solution (50% PEG300 (MCE,
HY-Y0873) + 50% saline), whereas the MMC rats received MMC (3 mg/kg,
once a week for 2 weeks, MCE, HY-13316). Fer-1 (1 mg/kg, Selleck,
S7243) was administered intraperitoneally every other day, with the
control group receiving saline. For the prevention model, saline or
Fer-1 was given beginning on the first day of MMC treatment for 35
days. For the therapeutic model, treatment started on day 21 post-MMC
treatment and continued every other day for 14 days. The HO-1 agonist
hemin (25 mg/kg, Sigma, H9039) and the HO-1 inhibitor Znpp (10 mg/kg,
MCE, HY-101193) were administered intraperitoneally every other day for
35 days, starting from the first day of MMC treatment, with the control
groups receiving saline or 50% PEG300 + 50% saline, respectively. At
the time of sacrifice, the rats were anaesthetized with 40 mg/kg sodium
pentobarbital and inhaling in 0.5% isoflurane, the anesthesia depth was
monitored with pedal reflex.
Generation of experimental PVOD mice and treatments
All the mice experiments performed in the present study were approved
by the Animal Institutional Review Boards (AIRB) of the Second
Affiliated Hospital of the Zhejiang University School of Medicine
(AIRB-2021-967 and AIRB-2024-327). A guide RNA (gRNA) targeting exon 33
of Eif2ak4 was designed with the sequence 5′-GCAAACAGAAAGCGTGTATTGG-3′
for use in CRISPR/Cas9 (Shanghai Model Organisms). The C57BL/6 J mice
with the mutation c.4413-4416del were identified and bred to obtain
homozygous mutants (Eif2ak4^K1488X/K1488X). Four-month-old C57BL/6 J
mice (25–30 g, equal male-to-female ratio) were assigned to the
following groups: the WT with or without hypoxia, Eif2ak4^K1488X/K1488X
with or without hypoxia. Hypoxia treatment (10% oxygen) for 6 weeks,
and then return to normoxia for 1 week. Fer-1 (1 mg/kg) was
administered intraperitoneally every other day; in the prevention
model, Fer-1 was administered from the first day of hypoxia for 42
days, and in the therapeutic model, Fer-1 was administered starting on
day 21 for 21 days. Hemin (25 mg/kg) and Znpp (10 mg/kg) were
administered intraperitoneally every other day, with the control groups
receiving saline. Mice were housed under standard conditions in
pathogen-free, individually ventilated microisolator cages in a room
with a 12 h light/dark cycle, and a temperature- and
humidity-controlled environment of 20–26 °C and 30–70% humidity, with
access to standard laboratory chow diet and water ad libitum. At the
time of sacrifice, the mice were anaesthetized with 0.15 mL of 1%
sodium pentobarbital and inhaling in 0.5% isoflurane, the anesthesia
depth was monitored with pedal reflex.
Bone marrow chimera mouse model
Bone marrow cells were isolated from the femur bone cavities of WT and
Eif2ak4^K1488X/K1488X mice, transplanted into 7-Gy irradiated WT
recipient mice via tail vein injection. Blood was collected 3 weeks
after bone marrow transplantation for DNA isolation with a commercially
available DNA isolation kit (Tiangen, DP304) and the Eif2ak4 transgene
was detected by PCR using the genotyping primers of
Eif2ak4^K1488X/K1488X mice to detect the transgene. The chimeric
recipient mice were subjected to hypoxia 3 weeks after transplantation.
Intratracheal administration of iron to mice
Ferric ammonium citrate (FAC, 50 mM, F3388, Sigma) was administered
intratracheally to 3-month-old C57BL/6 J WT and Eif2ak4^K1488X/K1488X
mice^[244]26. The mice were anaesthetized with 0.15 mL of 1% sodium
pentobarbital and inhaling 0.5% isoflurane, and 10 μL of PBS/FAC was
delivered intratracheally weekly for 2 weeks. Pulmonary function, the
RVSP, right ventricular hypertrophy (RVH), and lung histology were
evaluated 4 weeks after treatment initiation.
Hemodynamic measurements in rats and mice
Identical methods were employed for haemodynamic measurements in both
the rats and the mice. After the animals were anaesthetized, a Millar
catheter (mice PE-10, rats PE-90, Smith Medical) was inserted into the
right ventricle via the right jugular vein to measure the RVSP.
Continuous signals were collected using a physiological monitor for
data analysis. To assess the RVH index, the hearts were dissected, and
the right ventricle was isolated, washed with PBS, and weighed. The RVH
index was calculated with the following formula: RVH index = (right
ventricular weight/(left ventricle + septum weight)) × 100% (1). The
TPVRI was calculated using the following formula: TPVRI = RVSP
(mmHg)/CI (2), where CI is RVCO (mL/min) * 100/body weight (g) (3). The
RVSP was measured via right heart catheterization, and the RVCO was
estimated via echocardiography. For a statistical analysis of vascular
remodeling, immunohistochemical staining of α-SMA was performed, and
images were analyzed using the VS200 system. Rat vessels (70–250 μm)
were analyzed for lumen-to-total area ratios and media layer thickness,
respectively. Microvessels were classified on the basis of α-SMA
expression levels.
Immunohistochemical staining
The paraffin-embedded sections were dewaxed, hydrated, and subjected to
antigen retrieval. Endogenous peroxidase activity was quenched, and the
sections were incubated with primary antibodies (against GCN2, 4-HNE,
α-SMA, and HMOX1) overnight. Following secondary antibody incubation
and DAB chromogen development, the sections were counterstained with
haematoxylin, dehydrated, and mounted. Quantification of IHC images was
performed in a blinded manner using ImageJ (Fiji;
[245]https://imagej.nih.gov/ij/). Specifically, the intensity of
staining was scored, and the percent of positively stained areas was
calculated for analysis. Antibodies used for immunostaining are listed
in Supplementary Table [246]4.
Classification of arteries and veins
Arterial vessels accompany bronchial structures, demonstrating distinct
internal and external elastic laminae with densely arranged smooth
muscle cells in the tunica media. Venous vessels exhibit only an
external elastic lamina, featuring thinner vessel walls with loose
connective tissue and significantly larger luminal diameters compared
to corresponding arteries. Immunofluorescence was applied for venous
markers (NR2F2/α-SMA/CD31) and artery markers (α-SMA/CD31), showing
different types of vessels in the lungs.
Percent wall thickness of artery and vein
After fixing in 4% paraformaldehyde solution, embedding and sectioning,
the 5 µm slides of mouse pulmonary vessels (50–150 μm) were stained
with α-smooth muscle actin to access the medial
thickness^[247]51,[248]52. Double-blind analysis of sections was
completed by light microscopy (OLYMPUS VS120). The external vessel
perimeter (measuring from outside margin of external α-smooth muscle
actin lamina) and internal vessel perimeter (inside margin of internal
α-smooth muscle actin lamina) were measured using (OlyVIA). Fifteen
images of 50–100 µm vessels at 40× fields were acquired randomly from 5
to 7 mice in each group. Radius = perimeter/π/2 (4), and medial
thickness = external radius-internal radius (5). Standardized the
thicknesses by using the ratio of thickness to diameter, percent wall
thickness = 2*medial thickness/external diameter (6)^[249]53.
Prussian Blue staining with DAB enhancement
The paraffin-embedded sections were dewaxed and hydrated. The sections
were then stained with 2% potassium ferrocyanide and 2% hydrochloric
acid for 30 min, followed by three washes with distilled water. The
chromogen DAB was applied for 5‒10 min. The sections were
counterstained with haematoxylin for 1 min, blued in PBS and rinsed
with tap water. The sections were subsequently dehydrated in absolute
ethanol, cleared in xylene, and mounted with neutral balsam.
Heme quantification assay
Heme was quantified using the Heme Iron Assay Kit (Abcam, ab272534).
Tissue samples (0.1 g) were homogenized in 1 mL of PBS and centrifuged
at 13,500 x g for 10 min, after which the supernatants were collected.
The assay wells received 50 µL of water (blank), the calibration
solution, or a sample, followed by 200 µL of deionized water
(blank/calibration wells) or reaction reagent (sample wells). The
absorbance at 400 nm was measured after a 5-min incubation period. The
heme concentration was calculated as follows:
[MATH:
[heme]=(O<
mi>D_sample−OD_blank)<
mo>(OD_sta<
/mi>ndard−OD_blank)×62.5μM :MATH]
1
Measurement of tissue non-heme Iron
Frozen lung tissue was sectioned, weighed, and digested in NHI acid at
65–70 °C for ≥ 72 h. The homogenized tissue was centrifuged at
13,500 x g for 10 min. The supernatant was incubated with equal volumes
of BAT buffer and a standard iron solution at room temperature for
10 min. The absorbance was read at 535 nm, after which the iron
concentration was determined using a standard curve; the iron
concentration is expressed as µg of iron per g of wet tissue.
Lipid peroxidation (MDA) Assay
Lipid peroxidation was measured with an MDA Assay Kit (Biyuntian,
S0131S). Frozen lung tissue (0.1 g) that had been homogenized in 1 mL
of PBS was centrifuged at 13,500 x g for 10 min. An MDA working
solution was prepared and mixed with the lung homogenate, a standard,
or PBS, followed by heating in a boiling water bath for 15 min. The
samples were cooled and centrifuged, and the absorbance was measured at
532 and 450 nm.
Isolation and culture of mice primary bone marrow-derived macrophages (BMDMs)
Femurs and tibias from euthanized mice were flushed with 1640 medium,
and bone marrow cells were isolated (half male and half female). After
red blood cell lysis, the cells were resuspended in differentiation
types of medium (1640 medium, 10% serum, 15% L929 cell-conditioned
medium) and plated. Differentiation was maintained by changing the
medium every other day until day 7. BMDMs were harvested via 0.25%
trypsin. For the cell viability and ferroptosis assays, BMDMs were
treated with FAC or RSL3, and the staining assays were performed with
BODIPY581/591^[250]54.
Treatment of endothelial cells with macrophage supernatants
BMDMs differentiated for 7 days were treated with 300 µM FAC for 24 h,
and the supernatants were collected. The cell supernatant was filtered
through a 0.22 μm filter and treated with ECs for 72 h.
Preparation of lentivirus vectors
The gRNA targeting mouse exon 33 was designed at
[251]http://crispor.tefor.net/. The gRNA sequence was
5′-GCAGACAGAGAAGCGTGTGC-3′. This gRNA was subsequently cloned and
inserted into pLentiCRISPRv2 and transfected into 293 T cells along
with the packaging vector pSPAX2 and the envelope vector VSVG. The
supernatants were collected 48 h post-transfection, filtered, and
concentrated. The viral pellet was resuspended in the target cell
culture medium for subsequent infection.
Cultivation and treatment of endothelial cells and HT1080 cells
Human umbilical vein ECs (hUVECs, CBP60340), human pulmonary artery ECs
(hPAECs, Lonza, CC2530), and human pulmonary microvascular ECs (hPMECs,
Oligobio, oligo876L) were cultured in ECM medium with 5% FBS.
Lentivirus were used for GCN2 knockdown, which was confirmed by Western
blotting. ECs were preconditioned in low-serum medium before treatment
with FAC (Sigma, F3388), TNF (Abclonal, RP00993), GDF15 (R&D,
8146-GD-025), or CCL3 (Abclonal, RP01628). The cells were harvested for
protein or RNA analysis following treatment. HT1080 cells (CBP60250)
transfected with lentivirus and selected with puromycin were propagated
in high-glucose medium supplemented with 10% FBS. For ferroptosis
pathway detection, the cells were treated with FAC, and subsequent
analyses included protein extraction, Per’s DAB iron staining, and
calcein assays.
Protein extraction and quantification and Western blotting
Protein extraction was performed using the Pierce™ BCA Protein Assay
Kit (Thermo, 23227). Adherent cells and tissue samples were lysed and
homogenized in RIPA buffer. The supernatants were mixed with loading
buffer, boiled, and stored at −80 °C (long-term). Protein
quantification was performed with a BCA working solution and measuring
the absorbance at 562 nm after 30 min at 37 °C. For Western blotting,
samples were separated by SDS‒PAGE gels and then transferred to PVDF
membranes with standard operation. The membranes were blocked with
QuickBlock™ Western Blocking Buffer, and incubated overnight at 4 °C
with primary antibodies and followed with secondary antibody incubation
at room temperature. Detection was performed using enhanced
chemiluminescence (ECL, 1705060, Bio-Rad) reagent. Source data are
provided as a source data file. All antibodies in this study were
commercially purchased and have been validated by the vendors for
species and application. Validation data are available from the
respective vendor’s respective websites. Antibodies for western
blotting are listed in Supplementary Table [252]3.
RNA extraction, reverse transcription, and quantitative real-time PCR
(qRT-PCR)
Total RNA was extracted using TRIzol reagent (Genstar, P118). After
mixing lysate with chloroform, extracted RNA was incubated at −20 °C
overnight. Purified RNA was dissolved in RNase-free water. Reverse
transcription was carried with gDNA Clean Reaction Mix and M-MLV
reverse transcriptase with standard protocol (Accurate biology,
AG11728). Quantitative Real-time PCR was performed using ChamQ Blue
Universal SYBR qPCR Master Mix (Vazyme, Q312) on a Roche Light Cycler
480 instrument. The data were analyzed using Light Cycler 480 software.
Primer sequences used are listed in Supplementary Table [253]2.
Transwell endothelial cells and smooth muscle cells coculture assay
To investigate the effects of ECs on SMC proliferation and migration,
0.4 and 8 μm Transwell chambers (Falcon, 353095, and 353097) were used,
respectively. hUVECs were seeded in 24-well plates, starved in
high-glucose medium supplemented with 0.2% FBS for 24 h, and then
treated with 300 μM FAC for 72 h. SMCs were seeded in Transwell
chambers with high-glucose medium supplemented with 10% FBS and allowed
to attach, after which the medium was replaced with medium containing
0.2% FBS. Chambers were placed in the wells with the treated hUVECs for
24 h of coculture. SMCs were fixed with PFA, stained with DAPI, and
counted under a microscope.
Three-dimensional coculture of endothelial cells and smooth muscle cells
GFP-tagged hUVECs and red-stained SMCs were cocultured to form a 3D
system. GFP-positive hUVECs were selected and expanded. SMCs were
stained with PKH26. A mixture of hUVECs and SMCs was combined with ECM
and Matrigel (Corning, 356234), and the mixture was then dispensed into
μ-Slide chambers (Ibidi, 81506). After incubation, medium supplemented
with 0.2% FBS and 660 μM FAC was added, and the medium was replenished
daily. Images were captured using a confocal microscope, and the
vascular network was analyzed via ImageJ software.
Multicolor immunofluorescence staining
The tissue sections were deparaffinized, subjected to antigen retrieval
with EDTA solution, and blocked with 3% BSA. Primary antibodies were
applied overnight at 4 °C, followed by incubation with HRP-conjugated
secondary antibodies. TSA staining (servicebio, G1255) was performed
sequentially with multiple antibodies. The sections were stained with
DAPI and treated with an autofluorescence quencher. Images were
acquired using a confocal fluorescence microscope.
Calcein staining
Primary mice BMDMs and HT1080 cells were seeded in a 12-well plate and
treated with 100 μM FAC for 24 h. The cells were stained with calcein
AM (Beyotime, S2012), incubated in the dark at 37 °C for 10 min, and
washed with PBS. The fluorescence intensity was measured using a
microplate reader at an excitation wavelength of 494 nm and an emission
wavelength of 524 nm.
GSH/GSSG assay
Total and oxidized glutathione levels were measured using a GSH/GSSG
Assay Kit (Beyotime, S0053). The tissue samples were homogenized and
centrifuged, and the supernatant was used for the analysis. The samples
were treated to remove GSH, and the absorbance at an OD of 412 nm was
measured using prepared standards and reagents.
ELISAs
ELISAs for TNF, GDF15, and CCL3 were conducted using specific kits
(ABclonal, Human TNF, RK00030; Mouse TNF, RK00027; Human GDF15,
RK00086; Mouse GDF15, RK00369; Mouse CCL3, RK04218). The tissue samples
were homogenized, and the supernatants were collected. Standard curves
were prepared, samples and standards were incubated with biotinylated
antibodies and streptavidin-HRP, and the absorbance was measured at
OD450 nm with a reference at OD630 nm using a microplate reader.
Differentiation of venous endothelial cells
iPSCs were generated from PBMCs of a healthy donor (male) and PVOD
patient (male) following established protocols^[254]55. When
differentiation was initiated, iPSCs were dissociated into single cells
using TrypLE Express (Thermo Fisher, 12604013) and plated onto
Matrigel-coated plates at a density of 25,000–50,000 cells/cm². Freshly
seeded iPSCs were allowed to adhere and recover for 24 h in mTeSR
medium supplemented with 1 mM thiazovivin (Sigma, SML1045) before
initiating differentiation. Differentiation into venous ECs was
conducted in Chemically Defined Medium 2 (CDM2); the medium was
sterilely filtered through a 0.22 μm filter prior to use. Media were
exchanged at 24 h intervals with CDM2 basal medium supplemented with
various cytokines and chemicals. After 4 days, we yielded VECs^[255]56.
Then, iPSC-derived VECs were enriched for CD31^+ cells using CD31
microbead-based Magnetically Activated Cell Sorting (MACS, Miltenyi
Biotec, 130-091-935).
Statistics and reproducibility
Statistical analysis was conducted using GraphPad Prism v9.0.0 or R
software v4.2.3. The figure legends or Methods sections detail the
statistical tests conducted and the repeat numbers. P value < 0.05 was
considered statistically significant unless otherwise stated.
Reporting summary
Further information on research design is available in the [256]Nature
Portfolio Reporting Summary linked to this article.
Supplementary information
[257]Supplementary Information^ (10.2MB, pdf)
[258]Reporting Summary^ (135.8KB, pdf)
[259]Transparent Peer Review file^ (19.7MB, pdf)
Source data
[260]Source data^ (8.3MB, zip)
Acknowledgements