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Int J Med Sci 2024; 21(11):2189-2200. doi:10.7150/ijms.100127 This issue Cite

Research Paper


MITOCHONDRIAL ATP SYNTHESIS AND PROTON TRANSPORT SYNERGISTICALLY MITIGATE
OLIGODENDROCYTE PROGENITOR CELL DYSFUNCTION FOLLOWING TRANSIENT MIDDLE CEREBRAL
ARTERY OCCLUSION VIA THE PBX3/DGUOK/KIF21B SIGNALING PATHWAY

Yehai Li1 , Min Zhang1, Jinchuan Lin1, Hang Guo1, Hao Zhou2, Yong Jin1, Zhao
Yang1

1. Department of Neurosurgery, The Affiliated Guangdong Second Provincial
General Hospital of Jinan University, Guangdong Second Provincial General
Hospital, Guangzhou, Guangdong 510317, China.
2. School of Medicine, Southern University of Science and Technology, Shenzhen,
Guangdong, China.


✉ Corresponding author: Dr. Yehai Li: Department of Neurosurgery, Guangdong
Second Provincial General Hospital, Guangzhou, Guangdong 510317, P.R. China.
E-mail: liyehai@163.com.

Citation:

Li Y, Zhang M, Lin J, Guo H, Zhou H, Jin Y, Yang Z. Mitochondrial ATP Synthesis
and Proton Transport Synergistically Mitigate Oligodendrocyte Progenitor Cell
Dysfunction Following Transient Middle Cerebral Artery Occlusion via the
Pbx3/Dguok/Kif21b Signaling Pathway. Int J Med Sci 2024; 21(11):2189-2200.
doi:10.7150/ijms.100127. https://www.medsci.org/v21p2189.htm
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ABSTRACT

In the realm of this study, obtaining a comprehensive understanding of ischemic
brain injury and its molecular foundations is of paramount importance. Our study
delved into single-cell data analysis, with a specific focus on sub-celltypes
and differentially expressed genes in the aftermath of ischemic injury. Notably,
we observed a significant enrichment of the "ATP METABOLIC PROCESS" and "ATP
HYDROLYSIS ACTIVITY" pathways, featuring pivotal genes such as Pbx3, Dguok, and
Kif21b. A remarkable finding was the consistent upregulation of genes like Fabp7
and Bcl11a within the MCAO group, highlighting their crucial roles in regulating
the pathway of mitochondrial ATP synthesis coupled proton transport.
Furthermore, our network analysis unveiled pathways like "Neuron
differentiation" and "T cell differentiation" as central in the regulatory
processes of sub-celltypes. These findings provide valuable insights into the
intricate molecular responses and regulatory mechanisms that govern brain
injury. The shared differentially expressed genes among sub-celltypes emphasize
their significance in orchestrating responses post-ischemic injury. Our
research, viewed from the perspective of a medical researcher, contributes to
the evolving understanding of the molecular landscape underlying ischemic brain
injury, potentially paving the way for targeted therapeutic strategies and
improved patient outcomes.

Keywords: Ischemic Brain Injury, Single-Cell Analysis, Differentially Expressed
Genes, Molecular Pathways, Therapeutic Strategies




INTRODUCTION

Acute cerebral infarction (ACI) is one of the most common cerebrovascular
diseases, accounting for approximately 70% of acute cerebrovascular diseases [1,
2]. It results from various causes that lead to localized disruption of blood
supply in the brain, resulting in insufficient cerebral blood flow, ischemia,
and hypoxia in brain tissue [3]. This leads to localized necrosis and cerebral
softening, ultimately causing severe impairment of brain function. Cerebral
infarction has a high incidence, recurrence rate, mortality rate, and disability
rate, imposing a heavy burden on society and families [1, 2]. Based on previous
research, during the progression of cerebral infarction, processes such as
angiogenesis, blood-brain barrier disruption, and inflammatory responses
interact closely, collectively affecting neuronal survival, synaptic repair, and
regeneration. Rapid diagnosis and timely intervention for cerebral infarction
positively impact its prognosis. In current clinical practice, imaging
techniques are widely employed for the diagnosis of cerebrovascular diseases [1,
2]. However, they still face drawbacks like high costs, complex procedures, and
the need to move patients [4, 5]. Therefore, there is a pressing need to explore
more convenient and effective diagnostic and prognostic evaluation methods.

Under normal circumstances, mitochondrial mass and morphology balance are
maintained through mitochondrial autophagy. In general, a certain level of
mitochondrial autophagy contributes to maintaining mitochondrial quality and
adaptability to different environments. However, during the process of tissue
ischemia, there are significant changes in energy supply, and the role of
mitochondrial autophagy in preserving mitochondrial function and structure, as
well as the optimal intensity of mitochondrial autophagy, remains a subject of
debate [4, 5]. During cerebral hypoxia-ischemia, the disruption of brain blood
flow leads to mitochondrial dysfunction, reduced ATP production, and increased
production of reactive oxygen species (ROS). Energy depletion triggers a cascade
of reactions, disrupting ion gradients on the neuronal and glial cell membranes,
causing cell swelling and cytotoxic edema [6]. Additionally, calcium overload,
lipid peroxidation, and oxidative stress can lead to blood-brain barrier
disruption, brain edema, and neuronal death. Once the inflammatory response
cascade is activated, various cytotoxic substances, including nitric oxide (NO),
matrix metalloproteinase (MMP), tumor necrosis factor-alpha (TNF-α), and
interleukin-1 (IL-1), are released, leading to platelet aggregation,
microvascular blockage, further cell damage, and damage to the blood-brain
barrier (BBB) and extracellular matrix [6].

In recent years, the PINK1-Parkin pathway has been one of the most studied
pathways in mitochondrial research. Recent studies have indicated that AFPR can
significantly reduce neurological scores and infarct area in cerebral
ischemia-reperfusion rats, alleviate cortical neuronal apoptosis, and increase
hippocampal Nissl density. Furthermore, AFPR significantly promotes angiogenesis
by increasing microvessel density, VEGFA expression, SIRT3 expression, and
activating Pink1/Parkin-mediated mitochondrial autophagy [5, 7]. Additionally,
research by Yuan et al. found that extracellular signal-regulated kinase (ERK)
activation, dynamin-related protein 1 (Drp1)/mitochondrial fusion protein 2
(Mfn2)-dependent mitochondrial dynamics imbalance, and excessive autophagy are
involved in cerebral ischemia-reperfusion injury leading to neurologic damage
after cardiac arrest/cardiopulmonary resuscitation. In SH-SY5Y cell models, ERK
inhibition downregulates autophagy by reducing Drp1/Mfn2-dependent mitochondrial
fission, opposing mitochondrial dysfunction, and promoting neuronal survival.
Recent research also suggests that hypoxia induces mitochondrial biogenesis [5,
7]. Hypoxia increases the production of peroxisome proliferator-activated
receptor-gamma coactivator 1-alpha (PGC-1), downstream mitochondrial
transcription factors (mitochondrial transcription factor A and nuclear
respiratory factor 1), and heat shock protein 60 (HSP60) [4, 5]. This
groundbreaking discovery indicates that mitochondrial biogenesis is a novel
endogenous neuroprotective response. Mitochondrial dysfunction and excessive
oxidative stress play significant roles in ischemic cascade reactions. Recent
research suggests that mitochondrial biogenesis and ROS detoxification are two
important endogenous protective mechanisms in acute cerebral infarction and
chronic neurodegenerative diseases. However, their specific regulatory
mechanisms are not yet clear. Therefore, this study is based on single-cell
suspension and transcriptome chip integrative analysis to examine the core
regulatory cell subpopulations and regulators during the stages of cerebral
infarction.


METHODS


ETHICAL STATEMENT

This study adhered to the Declaration of Helsinki and the ethical guidelines of
Fujian Medical University Union Hospital. The Ethics Committee approved the
experimental protocols, with the reference number GSE208222.


SCRNA-SEQ ANALYSIS

In this study, we conducted a single-cell mining analysis, based on GSE208222
database[8, 9], to explore the gene expression profile of oligodendrocyte
progenitor cells (OPCs) isolated from the lateral ganglionic eminence of mice at
postnatal day 10 (p10). The mice were subjected to transient middle cerebral
artery occlusion (MCAO), and the OPCs were isolated two weeks post-MCAO. This
specific time point was chosen to capture the molecular changes in OPCs during
the recovery phase after ischemic insult. The methodology employed in this
analysis involved the isolation of OPCs from the lateral ganglionic eminence,
followed by the extraction of RNA to generate single-cell RNA-seq libraries
[10]. Subsequently, high-throughput sequencing was performed to obtain
comprehensive gene expression profiles at the single-cell level.

The obtained data were then preprocessed to filter out low-quality cells and
normalize expression levels. The intricate landscape of oligodendrocyte
progenitor cells (OPCs) was unveiled through a sophisticated analytical
duo—Principal Component Analysis (PCA) and t-Distributed Stochastic Neighbor
Embedding (t-SNE) [10]. The resulting PCA plot served as a visual
representation, offering insights into individual cell relationships and
unveiling latent structures. Complementing PCA, t-SNE, a non-linear
dimensionality reduction technique, provided a nuanced perspective by preserving
local relationships between cells. This approach, crucial for deciphering
complex cellular landscapes, created visually compelling t-SNE plots. These
plots accentuated distinct OPC subpopulations, capturing both global structures
and finer details of OPC diversity. Together, the synergistic use of PCA and
t-SNE not only transformed intricate gene expression data into accessible
visualizations but also facilitated a profound exploration of OPC heterogeneity.
This analytical tandem played a pivotal role in understanding how OPCs
dynamically respond to stimuli such as transient middle cerebral artery
occlusion (MCAO) [10].


DEGS DECTION

In the pursuit of unraveling the intricate molecular landscape shaped by
transient middle cerebral artery occlusion (MCAO) within oligodendrocyte
progenitor cells (OPCs), a rigorous two-fold analysis was undertaken. Firstly, a
detailed examination through differential expression analysis meticulously
identified genes undergoing significant shifts in expression levels in response
to the ischemic insult [11]. This granular exploration shed light on the
molecular protagonists orchestrating adaptive or pathological changes within the
OPC population post-MCAO.


GENE FUNCTIONAL ENRICHMENT ANALYSIS

Of the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG)
pathway enrichment analyses [11, 12]. Starting with the preparation of input
data, typically a list of differentially expressed genes (DEGs), researchers
install and load the necessary Bioconductor packages, including
'clusterProfiler.' Subsequently, gene IDs are converted using annotation
packages like 'org.Hs.eg.db' for human genes, and GO enrichment analysis is
executed using the 'enrichGO' function. The results are then visualized through
a bar plot, offering insights into significantly enriched GO terms [13]. For
KEGG pathway enrichment analysis, researchers employ the 'enrichKEGG' function,
and the outcomes are visualized using a bubble plot. Additional analyses, such
as the functional annotation chart created with the 'dotplot' function, further
enhance the understanding of enriched terms [14]. The final step involves
interpreting the results, focusing on the most significant GO terms and KEGG
pathways, thereby providing valuable insights into the functional implications
of DEGs in the biological system under study [15].


GENE SET ENRICHMENT ANALYSIS AND GENE SET VARIATION ANALYSIS

Expanding the analytical horizon, Gene Set Enrichment Analysis (GSEA) was
deployed, transcending individual genes to unveil broader biological
implications. GSEA scrutinized the distribution of genes within predefined sets
or pathways, unraveling enriched biological processes and signaling pathways
[16, 17]. This holistic approach provided a comprehensive panorama of how the
concerted activity of genes contributed to the functional landscape of OPCs in
the aftermath of MCAO [18]. The harmonized results from both the differential
expression analysis and GSEA forged a multidimensional understanding of the
molecular cascades triggered by MCAO in OPCs. This dual-pronged approach not
only spotlighted specific genes responding to the ischemic challenge but also
unveiled the intricate biological pathways and processes orchestrating the
cellular response [19].

Gene Set Variation Analysis (GSVA) is a computational method for assessing
biological pathway variations across samples. After organizing gene expression
data, installing necessary R packages, and loading gene sets, preprocessing
steps include data transformation and normalization [20]. The GSVA algorithm is
then applied to evaluate pathway activities, with an optional step for
differential analysis using 'limma' for statistical testing [21-23].
Visualization tools like heatmaps aid in understanding pathway variations.
Statistical analyses may involve tests and p-value adjustments, and results can
be integrated with clinical data for deeper insights. The methodology emphasizes
thorough documentation for reproducibility and the generation of concise reports
summarizing findings.


PROTEIN-PROTEIN INTERACTION NETWORKS CONSRUCTION

The STRING (Version: 12.0; https://string-db.org/) online platform serves as a
user-friendly gateway for conducting in-depth analyses of protein-protein
interactions (PPIs)[11, 24]. Upon accessing the STRING web portal, users can
input protein names, gene IDs, or sequences of interest, generating a visual PPI
network where protein nodes are connected by edges representing interactions.
This platform allows for the customization of network parameters, including
confidence score thresholds, refining the displayed interactions. Detailed
information about individual proteins, such as functional annotations and known
interactions, can be accessed by clicking on nodes within the network. STRING
offers robust visualization tools for tailoring the network layout,
color-coding, and node size, facilitating clear and interpretable
representations. Researchers can explore topological features, such as node
degrees and betweenness centrality, to identify hub proteins and central nodes
[25]. The platform also supports functional enrichment analyses, including Gene
Ontology terms and pathway enrichment, offering insights into biological
processes. Module detection algorithms aid in identifying cohesive protein
clusters, further elucidating the modular organization of the network.
Researchers can conveniently download visualized networks and tabular data for
further analysis. STRING integrates experimental validation tools, allowing
users to cross-reference predicted interactions with existing experimental data.


RESULTS


DECIPHERING POST-ISCHEMIC BRAIN RESPONSES: SINGLE-CELL RNA-SEQ OF NEURONAL
SUBPOPULATIONS

In our exploration of the single-cell dataset GSE208222, originating from murine
brains post-ischemic injury, a group of pivotal differentially expressed genes
has come to the forefront. Notably, genes such as Scgb1a1, Scgb3a2, Acta2,
Bpifa1, and Bc1 have displayed significant alterations in their expression
patterns (Figure 1A). The dataset can be broadly classified into distinct
cellular subpopulations, encompassing Astrocytes, Endothelial cells,
Fibroblasts, Neurons, and Oligodendrocytes (Figure 1B). Of particular interest,
the Neurons subpopulation can be further subdivided into five distinct neuronal
subgroups (Figure 1C). A thorough analysis of these neuronal subgroups has
unveiled captivating dynamics in gene expression. Within Neu-Sub1, there is
prominent upregulation of Stmn2 and Btg1, while Fabp7, Ptprz1, Cspg5, and Olig1
are among the downregulated genes. In Neu-Sub2, upregulated genes include Cspg5,
Olig1, and C1ql1, with Dlx6os1, Igfbpl1, Tubb3, Stmn1, and Stmn1 notably
downregulated. Neu-Sub3 exhibits upregulation in genes such as Hist1h2ap, Hmgb2,
Pclaf, Top2a, Ube2c, and Rrm2, while downregulated genes comprise C1ql1, Olig1,
Meg3, and Cspg5. In Neu-Sub4, genes like Tbr1, Eomes, and Sema3c are primarily
upregulated, while Meg3, Olig1, Ptprz1, and Cspg5 show significant
downregulation. Neu-Sub5, in contrast, demonstrates upregulation of genes
including Lhx6, Nkx2-1, Epha5, Npy, and Ripor2, while Olig1, Fabp7, Meis2, Dbi,
and Ptprz1 are observed in a downregulated state (Figure 1D).


ANALYSIS OF DIFFERENTIAL GENE EXPRESSION AND KEY REGULATORY PATHWAYS IN NEU-SUB1
AND NEU-SUB2

In our investigation of the single-cell dataset, focusing on the comparison
between Neu-Sub1 and Neu-Sub2, we identified distinctive differential gene
expression patterns grouped into three main clusters. Within Kmeans-Cluster1, we
observed the upregulation of genes like Tubb3, Meis2, Sp9, Arx, and Sox11,
contrasted by the downregulation of Matn4, Bcan, Cd9, Fabp7, and Ptprz1. In
Kmeans-Cluster2, genes like Stmn2, Tiam2, Pfn2, Islr2, and Rnd3 were
upregulated, while Luzp2, Ntm, Ramp1, Phlda1, and Pcsk1n were notably
downregulated. Kmeans-Cluster3 displayed upregulation in genes such as Stmn1,
Ccnd2, Map1b, Igfbpl1, and Btg1, with Cdo1, Mt3, Rgcc, and S100a1 among the
downregulated genes (Figure 2A). Furthermore, KEGG pathway enrichment analysis
revealed that these differentially expressed genes were primarily associated
with pathways such as KEGG_MAPK_SIGNALING_PATHWAY, KEGG_HUNTINGTONS_DISEASE,
KEGG_ENDOCYTOSIS, KEGG_ALZHEIMERS_DISEASE, and KEGG_FOCAL_ADHESION, providing
valuable insights into the underlying biological processes and signaling
pathways (Figure 2B). Additionally, GO analysis indicated significant
enrichments in various biological processes (BP), including gliogenesis, glial
cell differentiation, and axonogenesis. Cellular component (CC) terms such as
myelin sheath, postsynaptic specialization, and asymmetric synapse exhibited
substantial enrichment. Molecular function (MF) terms, encompassing cell
adhesion molecule binding, integrin binding, and calcium-dependent protein
binding, were also significantly enriched, highlighting the intricate molecular
mechanisms at play (Figure 2C). Notably, GSEA analysis identified pivotal
pathways like CELL MORPHOGENESIS INVOLVED IN NEURON DIFFERENTIATION,
ENSHEATHMENT OF NEURONS, and NEURON PROJECTION GUIDANCE, shedding light on the
primary processes driving neuronal damage post-ischemic injury (Figure 2D).


ANALYSIS OF DIFFERENTIAL GENE EXPRESSION AND KEY REGULATORY PATHWAYS IN NEU-SUB1
AND NEU-SUB3

Regarding the comparison between Neu-Sub1 and Neu-Sub3, we unearthed significant
differential gene expression patterns grouped into three primary clusters.
Within Kmeans-Cluster1, we noted the upregulation of Pbx3, while Hist1h2ab,
Selenoh, Ran, and Hist1h2ap showed notable downregulation. Kmeans-Cluster2
revealed an upregulation of Btg1, with Apoe, Fabp7, Tubb4b, Dbi, and Ascl1
downregulated. Kmeans-Cluster3 exhibited downregulation of genes such as Cenpf,
Ube2c, Top2a, and Hmgb2(Figure 3A).

 Figure 1 

Deciphering Post-Ischemic Brain Responses: Single-Cell RNA-Seq of Neuronal
Subpopulations. A highlights the primary differentially expressed genes
post-ischemic injury, featuring key players such as Scgb1a1, Scgb3a2, Acta2,
Bpifa1, and Bc1. B and C categorize cellular subpopulations into Astrocytes,
Endothelial cells, Fibroblasts, Neurons, and Oligodendrocytes. Notably, Neurons
further divide into five distinct neuronal subgroups. D provides a detailed view
of the differential gene expression within these neuronal subgroups, showcasing
the major upregulated and downregulated genes.

 Figure 2 

Analysis of Differential Gene Expression and Key Regulatory Pathways in Neu-Sub1
and Neu-Sub2. A showing the differential gene expression analysis between
Neu-Sub1 and Neu-Sub2 reveals distinct clusters of genes distributed across
three main clusters. B presenting the KEGG pathway enrichment analysis
demonstrates a significant enrichment of differentially expressed genes in
pathways such as KEGG_MAPK_SIGNALING_PATHWAY, KEGG_HUNTINGTONS_DISEASE,
KEGG_ENDOCYTOSIS, KEGG_ALZHEIMERS_DISEASE, and KEGG_FOCAL_ADHESION. Panel C
portrays the outcomes of Gene Ontology (GO) analysis, presenting enriched
biological processes (BP), cellular components (CC), and molecular functions
(MF) related pathways. D showing the results GSEA unveil prominent pathways
associated with neuronal damage post-ischemic injury, including CELL
MORPHOGENESIS INVOLVED IN NEURON DIFFERENTIATION, ENSHEATHMENT OF NEURONS, and
NEURON PROJECTION GUIDANCE.

Furthermore, our KEGG pathway enrichment analysis unveiled that these
differentially expressed genes were predominantly associated with pathways like
KEGG_CELL_CYCLE, KEGG_DNA_REPLICATION, and KEGG_GAP_JUNCTION, providing crucial
insights into the biological processes and signaling pathways at play (Figure
3B). Additionally, our GO analysis indicated substantial enrichments in various
biological processes (BP), encompassing chromosome segregation, sister chromatid
segregation, and mitotic nuclear division. In terms of cellular components (CC),
there was significant enrichment in terms like chromosome, centromeric region,
chromosomal region, and condensed chromosome, centromeric region. Molecular
functions (MF) such as tubulin binding, microtubule binding, and single-stranded
DNA helicase activity also showed notable enrichment, underscoring the complex
molecular mechanisms involved (Figure 3C). Of particular significance, our GSEA
analysis highlighted critical pathways such as NEURON DEVELOPMENT, NEURON
DIFFERENTIATION, and NEURON PROJECTION, shedding light on the primary processes
driving neuronal damage post-ischemic injury (Figure 3D).

 Figure 3 

Analysis of Differential Gene Expression and Key Regulatory Pathways in Neu-Sub1
and Neu-Sub3. Panel A illustrates the outcomes of the differential gene
expression analysis between Neu-Sub1 and Neu-Sub3, revealing the primary
differentiation into three distinct clusters of differentially expressed genes.
In Panel B, the KEGG pathway enrichment analysis showcases a predominant
enrichment of differentially expressed genes in pathways such as
KEGG_CELL_CYCLE, KEGG_DNA_REPLICATION, and KEGG_GAP_JUNCTION. C presents the
results of Gene Ontology (GO) analysis, highlighting the enrichment of
biological processes (BP), cellular components (CC), and molecular functions
(MF) related pathways. The findings from GSEA are depicted in Panel D,
identifying NEURON DEVELOPMENT, NEURON DIFFERENTIATION, and NEURON PROJECTION as
the primary pathways associated with neuronal damage post-ischemic injury.

 Figure 4 

Hub pathway detection in the procesiion of post-ischemic brain responses. A
highlights the significant enrichment of the ATP METABOLIC PROCESS pathway in
the differential gene expression analysis between sub-celltype 1 and
sub-celltype 2. In Panel B, the enrichment of ATP HYDROLYSIS ACTIVITY is notably
observed in the differential gene expression analysis between sub-celltype 1 and
sub-celltype 3.C demonstrates the identification of 34 common differentially
expressed genes among sub-celltype 1 vs sub-celltype 2, sub-celltype 1 vs
sub-celltype 3, and GSE61616 DEGs. D primarily showcases the collective
expression changes of the 34 identified genes across different sub-celltype
comparisons.E presents the results of pathway enrichment network analysis,
revealing key pathways such as Neuron differentiation, Neuron projection
morphogenesis, and T cell differentiation as central clusters actively involved
in regulatory processes.


HUB MARKERS DETECTION AND VALIDATION

In our comparative analysis between sub-celltype 1 and sub-celltype 2, a
noteworthy enrichment was observed in the "ATP METABOLIC PROCESS" pathway. Key
regulatory genes within this pathway, including Dguok, Tgfb1, Pgk1, Hspa8, and
P2rx7, exhibited significant differential expression (Figure 4A). Similarly, in
the comparison between sub-celltype 1 and sub-celltype 3, we identified a
distinct enrichment pattern in the "ATP HYDROLYSIS ACTIVITY" pathway, featuring
genes such as Kif21b, Ddx17, Ddx5, Tcp1, and Cct5 (Figure 4B). By intersecting
the results from sub-celltype 1 vs. sub-celltype 2, sub-celltype 1 vs.
sub-celltype 3, and GSE61616 DEGs, we uncovered 34 common differentially
expressed genes (Figure 4C). Within the MCAO group, notable upregulated genes
included Fabp7, Tmem176b, Cdca7, Gltp, and Cd1d1, while downregulated genes
encompassed Sox11, Meis2, Slc32a1, Bcl11b, and Dlx5, among others (Figure 4D).
Pathway enrichment network analysis revealed key clusters of pathways involved
in regulatory processes (Figure 4E)., such as "Neuron differentiation," "Neuron
projection morphogenesis," "T cell differentiation," "Synaptic signaling," and
"ATP metabolic process."

 Figure 5 

Key Regulatory Genes detection in the procesiion of post-ischemic brain
responses. A highlights the pronounced enrichment of the "MITOCHONDRIAL ATP
SYNTHESIS COUPLED PROTON TRANSPORT" pathway within ATP generation-related
pathways. B to F collectively underscore pivotal genes, including Pcp4, Sox11,
Bcl11a, Mycn, and Bcl11b, identified as major players actively participating in
the regulatory processes.

Within the context of pathways related to ATP generation, it's noteworthy that
the "MITOCHONDRIAL ATP SYNTHESIS COUPLED PROTON TRANSPORT" pathway stands out as
significantly enriched (Figure 5A). This pathway is predominantly governed by
key regulatory genes such as Pcp4, Sox11, Bcl11a, Mycn, and Bcl11b.
Interestingly, in the GSE61616 gene set, these target genes consistently exhibit
elevated expression levels within the MCAO group (Figure 5B-F). This consistent
upregulation underscores their central role in governing the "MITOCHONDRIAL ATP
SYNTHESIS COUPLED PROTON TRANSPORT" pathway.


DISCUSSION

Mitochondrial energy metabolism plays a pivotal role in the microenvironment of
the nervous system. Numerous past studies have delved into the role of
mitochondrial activity in the process of ischemic stroke, including energy
sourcing and the generation of inflammatory mediators. Mitochondria primarily
generate the majority of ATP through the mitochondrial respiratory chain (MRC)
and oxidative phosphorylation (OXPHOS), serving as the cellular powerhouse [26].
Their double-membrane structure and rich enzyme content make them central to
intracellular biosynthesis. Given the high energy demands of neurons, they are
more susceptible to damage and death due to mitochondrial dysfunction.
Additionally, mitochondria produce large molecular precursors of metabolism,
such as lipids, proteins, DNA, RNA, as well as metabolic byproducts like
reactive oxygen species (ROS) and ammonia, and they have mechanisms for waste
clearance or utilization. Significant changes occur in mitochondria under
ischemic and hypoxic conditions, including calcium influx, mitochondrial
permeability transition pore (mPTP) opening, reactive oxygen species (ROS)
generation, DNA damage and mutations, mitochondrial dynamics imbalance, and
mitochondrial positioning anomalies [27, 28]. These changes are closely
associated with patients with ischemic stroke and various animal models.
Mitochondria, acting as receptors for various stimuli, trigger both
caspase-independent (AIF, apoptosis-inducing factor) and caspase-dependent
(cytochrome c) cell death. Ischemic and hypoxic conditions promote these
processes, leading to neuronal necrosis and apoptotic death. Inflammation is
another key factor in the pathophysiology of brain ischemia [28, 29]. Glial cell
activation, peripheral leukocyte infiltration, and damage-associated chemicals
such as high-mobility group proteins, nucleotides, nucleic acid fragments, and
purines trigger inflammatory responses following ischemia. Mitochondria also
play a role in these inflammatory changes. Considering the vital role of
mitochondria in the process of ischemic stroke, we have identified a series of
differentially expressed genes involved in the development and progression of
the disease through bioinformatics screening.

BCL11B, a zinc finger transcription factor, is primarily responsible for
establishing proper connectivity in subcortical neurons, particularly in the
fifth-layer motor neurons [30]. BCL11B is also associated with the
differentiation of spiny neurons in the striatum during embryonic development.
Furthermore, in the adult brain, BCL11B is expressed in the basal ganglia, fifth
cranial nerve nucleus, olfactory bulb, and spinal cord. Early studies found that
BCL11B (B-cell CLL/lymphoma 11B) is crucial for spinal cord spiny neuron
differentiation, striatal patch development, and striatal cell structure
establishment. Moreover, there are reports suggesting that BCL11B serves as a
novel regulatory factor in the brain-derived neurotrophic factor (BDNF)
signaling pathway [30], which is disrupted in many neurological disorders.
Recent research, combining expression studies with in vivo MRI and neural
functional deficit score monitoring in individual animals with ischemic lesions,
concludes that BCL11B expression is positively correlated with post-ischemic
neurorecovery, indicating its beneficial role in injury repair following
ischemia [31, 32]. PCP4, also known as PEP-19, is a highly expressed protein in
Purkinje cells. PCP4 belongs to the calmodulin family and possesses homologous
calmodulin (CaM) binding domains, with anti-apoptotic and calmodulin-binding
functions [33, 34]. It is reported that PCP4 is also expressed in the olfactory
cortex of non-human primates, though its function in these brain regions remains
unclear. However, this protein is associated with the regulation of calcium and
calcium-dependent signal transduction, often achieved through restricting
calcium and calmodulin activity by interacting with CA2 and other calmodulins
[33, 35]. Here, PCP4 actively regulates neurotransmitter release and axon growth
in cell lines. Additionally, PCP4 mRNA and protein levels can be regulated by
steroid hormones such as estrogen and steroid hormone receptors. The PCP4 gene
is located on chromosome 21, particularly in the critical region for Down
syndrome (DS), suggesting a direct correlation with the pathogenesis of DS[34,
36]. Sox11 plays a pivotal role in regulating neuronal survival, making it a
crucial regulatory factor in the development of sensory neurons and a factor in
tumor stem cells [37]. In the central nervous system, overexpression of Sox11
promotes neuronal maturation in developing chicken neural tubes. Sox11 is
abundantly expressed during embryonic development but has very low expression
levels in adult sensory ganglia (Tanabe, 2003). Following peripheral nerve
injury, Sox11 mRNA is upregulated in adult dorsal root ganglia (DRG).
Overexpression of Sox11 enhances excitability in dentate gyrus (DG) granule
cells and reduces levels of various potassium channel subunits, indicating the
critical importance of Sox11 activity in regulating the plasticity of DG neurons
[38, 39]. Our research findings suggest that Sox11 is crucial for neuronal
survival under oxygen-glucose deprivation/reoxygenation (OGD/R) conditions and
provides protection against stroke-induced damage. Furthermore, Sox11 mediates
neuroprotection by minocycline under OGD/R conditions. BCL11A belongs to a
protein transcription factor family containing C2H2 zinc finger domains and is
highly expressed in the central nervous system [32, 40, 41]. It is indispensable
for neural development and has been found to be upregulated at early time points
after nerve injury. Lack of BCL11A in neurons of the central nervous system
leads to differentiation interruption and reduced free radical migration,
thereby affecting morphogenesis and neural innervation. Reports suggest that in
the central nervous system, BCL11 controls polarity and migration of upper-layer
neurons during neocortical development. Studies have demonstrated that BCL11A
may mediate Schwann cell activation and peripheral nerve regeneration by binding
to the promoter of nuclear receptor subfamily 2 group F member 2 (Nrf2) [32, 40,
41]. Thus, BCL11A is crucial for Schwann cell activation and peripheral nerve
regeneration. MYCN is a member of the MYC proto-oncogene family, which also
includes MYC and MYCL, encoding a basic helix-loop-helix-leucine zipper
(bHLH-LZ) transcription factor [42, 43]. Overexpression of the MYCN gene is a
characteristic feature of many embryonal brain tumors, leading to enhanced cell
proliferation and cell cycle disruption. Early studies suggest that
overexpression of MYCN in neuroblastoma cells results in a transcriptome rich in
typical MYC target genes, including those involved in ribosome biogenesis and
protein synthesis [43, 44]. MYCN functions as a transcriptional regulator of
many target genes involved in critical cellular processes, including but not
limited to metabolism. A functional gene set characteristic of MYCN has been
identified in a neuroblastoma cell line, suggesting that MYCN suppresses genes
related to neuronal differentiation [43, 45].

In summary, our current research has preliminarily confirmed the critical roles
of core genes, including Bcl11b, Pcp4, Sox11, Bcl11a, and Mycn, in ischemic
stroke disease. Further extensive research is required to validate these
findings and potentially provide new insights for the treatment of ischemic
stroke.


ACKNOWLEDGEMENTS


AUTHOR CONTRIBUTIONS

YH, MZ, JC, and HG performed experiments; YH, HZ, YJ and ZY participated
conceptualization and manuscript preparation. All authors approved the final
submission.


DATA AVAILABILITY

Data associated with this work can be obtained from the corresponding authors
upon reasonable request.


COMPETING INTERESTS

The authors have declared that no competing interest exists.


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AUTHOR CONTACT

Corresponding author: Dr. Yehai Li: Department of Neurosurgery, Guangdong Second
Provincial General Hospital, Guangzhou, Guangdong 510317, P.R. China. E-mail:
liyehai@163.com.

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Received 2024-6-26
Accepted 2024-8-2
Published 2024-8-13

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CITATION STYLES

APA Copy

Li, Y., Zhang, M., Lin, J., Guo, H., Zhou, H., Jin, Y., Yang, Z. (2024).
Mitochondrial ATP Synthesis and Proton Transport Synergistically Mitigate
Oligodendrocyte Progenitor Cell Dysfunction Following Transient Middle Cerebral
Artery Occlusion via the Pbx3/Dguok/Kif21b Signaling Pathway. International
Journal of Medical Sciences, 21(11), 2189-2200.
https://doi.org/10.7150/ijms.100127.

ACS Copy

Li, Y.; Zhang, M.; Lin, J.; Guo, H.; Zhou, H.; Jin, Y.; Yang, Z. Mitochondrial
ATP Synthesis and Proton Transport Synergistically Mitigate Oligodendrocyte
Progenitor Cell Dysfunction Following Transient Middle Cerebral Artery Occlusion
via the Pbx3/Dguok/Kif21b Signaling Pathway. Int. J. Med. Sci. 2024, 21 (11),
2189-2200. DOI: 10.7150/ijms.100127.

NLM Copy

Li Y, Zhang M, Lin J, Guo H, Zhou H, Jin Y, Yang Z. Mitochondrial ATP Synthesis
and Proton Transport Synergistically Mitigate Oligodendrocyte Progenitor Cell
Dysfunction Following Transient Middle Cerebral Artery Occlusion via the
Pbx3/Dguok/Kif21b Signaling Pathway. Int J Med Sci 2024; 21(11):2189-2200.
doi:10.7150/ijms.100127. https://www.medsci.org/v21p2189.htm

CSE Copy

Li Y, Zhang M, Lin J, Guo H, Zhou H, Jin Y, Yang Z. 2024. Mitochondrial ATP
Synthesis and Proton Transport Synergistically Mitigate Oligodendrocyte
Progenitor Cell Dysfunction Following Transient Middle Cerebral Artery Occlusion
via the Pbx3/Dguok/Kif21b Signaling Pathway. Int J Med Sci. 21(11):2189-2200.

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