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. 2024 Sep 30;15(20):3713–3723. doi: 10.1021/acschemneuro.4c00329

Comparison of Neurogenesis Promotion Effects between Cinnamoylquinic Acids in Neural Stem Cells from Adult Mice Brains

Hongyu Lin †, Kazunori Sasaki ‡,§, Farhana Ferdousi †,‡,∥, Hiroko Isoda †,‡,§,∥,*
PMCID: PMC11487612  PMID: 39348888

Abstract

graphic file with name cn4c00329_0007.jpg

Caffeoylquinic acids (CQAs) and feruloylquinic acids (FQAs), as cinnamoylquinic acids, have neurogenesis promotion effects. We studied for the first time the neurogenesis-enhancing effect of 3,4,5-tri-feruloylquinic acid (TFQA) compared to 3,4,5-tri-caffeoylquinic acid (TCQA), which has a similar structure, and explored their different cellular and molecular mechanisms in neural stem cells (NSCs) of mice brains. After 2 weeks of incubation, we first assessed the number and size of NSCs in TCQA and TFQA treatments. In NSCs treated for TCQA and TFQA, the NSC proliferation gene expression as well as neuronal and glial cell differentiation gene expressions improved. In the microarray assay, the erythroblastic oncogene B (ErbB) signaling pathway, as the common signaling of TCQA and TFQA treatments, was focused on and discussed. In our study, TCQA and TFQA treatments in NSCs showed a significant performance on improving synapse growth and neurogenesis compared with no treatment of NSCs. The two treatments in NSCs also had a significant activation of the ErbB signaling pathway, protein kinase B (AKT), and mitogen-activated protein kinase (MAPK) kinases. In particular, the TCQA-expressed proliferation gene myelocytomatosis oncogene (Myc) had the greatest connections significantly. TFQA treatment remarkably regulated the differentiation gene jun proto-oncogene (Jun), which was the gene with greatest direct relations, while Myc was also induced in TFQA treatment. In the overall quantitative real-time polymerase chain reaction (PCR) assay, TFQA had more outstanding neural proliferation and differentiation capabilities than TCQA in NSCs. Our study suggests that TFQA has greater therapeutic potential in neurogenesis promotion and neurodegenerative diseases compared with TCQA.

Keywords: cinnamoylquinic acids; 3,4,5-tri-feruloylquinic acid; neural stem cells; neurospheres; microarray; neurogenesis

Introduction

Cinnamoylquinic acids make up a group of naturally occurring compounds belonging to the family of phenolic acids. They are derivatives of quinic acid, which is a cyclic polyol compound that is found in various plants. Caffeoylquinic acids (CQAs), as specialized natural plant bioactive metabolites and a subset of cinnamoylquinic acids, are found in a wide range of foods, including coffee beans, potatoes, popular citrus fruits, chrysanthemum, kuding tea, and honeysuckle flower.1 CQAs and their derivatives have anticancer, antioxidant, anti-inflammatory, antibacterial, antiparasitic, antiviral, and antidiabetic effects.2 The CQA derivative-rich sweet potato extract has a neuroprotective effect and improves spatial learning and memory in vivo.3 The mRNA expression of the glycolytic enzyme (PGK1) and intracellular adenosine triphosphate (ATP) levels are increased in CQA-treated SH-SY5Y cells, and CQA improves spatial learning and memory in senescence-accelerated mouse-prone (SAMP) 8 mice, as well as overexpression of PGK1 mRNA.4 Among CQAs, 3,4,5-tri-caffeoylquinic acid (TCQA) treatment increases the glial fibrillary acidic protein and neurons in vivo (Figure 1A). TCQA induces cell cycle arrest at G0/G1 and bone morphogenetic protein signaling in aging mice.5 It has been proven that TCQA has huge potential to protect neural functions. Another subset of cinnamoylquinic acids, feruloylquinic acids (FQAs) from coffee beans, are also a class of biologically active phenolic compounds.6 There is less research on FQAs, but they have been found to improve metabolism and have antioxidant and anti-inflammatory effects by the sulfation of ferulic acid (FA).7 FA, a methylated caffeic acid, has antidepressant effects via enhancement of energy metabolism and dopamine in vivo.8 FQAs have a neuroprotective effect by upregulating the expression of endogenous antioxidant enzymes and activating the nuclear factor erythroid 2-related factor 2 (Nrf2) pathway.9 As one of the FQAs, 3,4,5-tri-feruloylquinic acid (TFQA), in which all caffeoyl groups of TCQA are replaced by feruloyl groups, was expected to promote neurogenesis (Figure 1B). However, because of its rarity, there have been no report on TFQA, including its neural functions. Therefore, we were interested in the neurogenic effect of TFQA.

Figure 1.

Figure 1

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Structures of (A) TCQA and (B) TFQA.

Neurogenesis is a lifelong process in mammals, and neural stem cells (NSCs) provide plasticity to brains. During the formation of the central nervous system (CNS), NSCs proliferate and differentiate to generate neurons during the process of neurogenesis. Adult neurogenesis depends on the persistence of NSCs.10 As a leading cause of morbidity and disability, neurodegenerative diseases adversely affect the lives of an increasing number of people in the world, causing a loss of neurons in the CNS and peripheral nervous system (PNS). Adult neurogenesis deficiency is considered a common hallmark of different age-related neurodegenerative diseases. Degeneration of adult neurogenesis is a common hallmark of different neurodegenerative diseases, including Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, and ataxias.11 Because of the loss of neurons and the self-renewal ability, there are deficits of speech and emotion cognitions in left anterior insular cortex atrophy, while in right dorsal atrophy, there are deficits of perception cognition.12 In this regard, compounds that can effectively restore distinct aspects of adult neurogenesis have attracted a strong interest from an increasing number of researchers.

In the present study, we evaluated the effect and potential molecular mechanisms of TCQA and TFQA on enhancing neurogenesis in adult mice NSCs. Our results suggested that cinnamoylquinic acids TCQA and TFQA may provide potential therapeutic strategies for neurogenesis promotion, specially TFQA.

Results and Discussion

TCQA and TFQA Increase the Rate of Neurosphere Formation

To interpret the role of TCQA and TFQA in NSCs, we first evaluated the ability of adult NSCs to generate neurospheres, a state of progenitor cell activation. TCQA and TFQA treatments increased the size of the neurosphere compared with control cultures in vitro (Figure 2A). The neurosphere sizes in 1 to 10 μM TCQA and TFQA treatment groups were increased significantly (Figure 2B). The neurosphere sizes in 1 μM TCQA treatment and 5 μM TFQA treatment were the largest, with sizes of 598.75 and 646.6 μm2, respectively, while the neurosphere size in 1 μM TFQA was 608 μm2. There were significant neurosphere numbers in the 1 μM TFQA treatment (Figure S1). Neurospheres consistently maintain the capability to differentiate along all of the three neural lineages: neurons, oligodendrocytes, and astrocytes. NSCs provide a promising approach for studying the neurogenesis, modeling, and pathogenesis of central nervous system diseases and establishing drug screening approaches. NSCs can secrete several neurotrophic factors to promote the repair of damaged cells, thereby strengthening the networks between synapses and ultimately generating new neural lines.13 The neurosphere is one form of NSCs. Neurospheres have the significant capability to differentiate into neurons and glia cells.14 Overall, this differentiation potential through increased self-renewal acknowledges that TCQA and TFQA may promote multiple lineage possibilities.

Figure 2.

Figure 2

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Effect of TCQA and TFQA on the number and size of NSCs (n = 3 in each group). (A) Images of NSCs treated with different concentrations of TCQA and TFQA, cell scale bar = 100 μm. (B) Size of NSCs treated with TCQA and TFQA. Data are expressed as the mean ± standard deviation (SD) of three independent experiments. ****p < 0.0001, ***p < 0.001, **p < 0.01, and *p < 0.05.

TCQA and TFQA Regulate the Transcriptome of NSCs

To explore the potential of TCQA and TFQA on improving neurogenesis, the microarray assay for samples with 72 h treatment time was performed. The overall microarray analysis workflow can be found in Figure 3A. Four samples of TCQA treatment, four samples of TFQA treatment, and three control samples were analyzed. Differentially expressed genes (DEGs) of TCQA treatment groups compared with control groups were expressed as “TCQA.” DEGs of TFQA treatment groups compared with control groups were expressed as “TFQA.” First, as shown in Figure 3B, the red dots represent upregulated DEGs, and the green dots represent downregulated DEGs. The X-axis represents the magnitude of the FC value, while the Y-axis corresponds to the negative logarithm of the P-value. The volcano plots for each data set show the distributions of significant DEGs between TCQA and no treatment and TFQA and no treatment comparisons [P-value < 0.05 and fold change (FC) > 1.2]. The DEGs found were 624 upregulated and 647 downregulated in TCQA. DEGs with 545 upregulated and 504 downregulated were found in TFQA. In TCQA, there were 139 upregulated and 133 downregulated DEGs with a FC more than 1.2, while there were 122 upregulated and 90 downregulated DEGs with a FC more than 1.2 in TFQA. In addition, circos plots show how genes in the input gene list overlap (Figure 3C). A greater number of purple links and a longer dark orange arc implies a greater overlap among the input gene lists. The biological processes (BPs), molecular function (MF), and cellular component (CC) enriched in Gene Ontology (GO) analysis are shown in Figure S2. There were 201 common upregulated DEGs, while 432 and 344 DEGs were upregulated in TCQA and TFQA, respectively. Next, we used the MCODE algorithm in Metascape analysis, which was then applied to the network to identify neighborhoods where proteins are densely connected, to research the common pathways of TCQA and TFQA. As shown in Figure 3D, the Ras signaling pathway was the significant common signaling, with a −log10 (P-value) of 3.4. As one of the common BPs, muscle structure development is involved in the formation, maturation, maintenance, and regeneration of neuromuscular junctions, and it ultimately leads to synapse formation (Figure 3E).15 Pathway mitochondrial translation, with a −log10 (P-value) of 7.8, also modulates neuronal activity (Figure 3F). By generating energy ATP and nicotinamide adenine dinucleotide (NAD)+, mitochondria play an important role in controlling fundamental processes of neuroplasticity, including neural differentiation, neurite outgrowth, neurotransmitter release, and dendritic remodeling.16 Finally, BP regulation of the mitogen-activated protein kinase (MAPK) cascade was enriched in shared DEGs of TCQA and TFQA significantly (Figure 3G). In mature neurons, the MAPK cascade is stimulated by excitatory glutamatergic signaling and may therefore have a role in synaptic plasticity.17 Overall, the potential for neural functions of TCQA and TFQA on regulating the transcriptome in NSCs was shown.

Figure 3.

Figure 3

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Overview of DEGs by TCQA and TFQA treatments. (A) Overall flowchart of the microarray analysis. (B) Volcano plots displaying DEGs in TCQA and TFQA treated conditions compared to control. Column charts showing the number of DEGs in different threshold ranges. Red represents upregulated DEGs andgreen represents downregulated DEGs. (C) Circos plots showing the DEG overlap of TCQA and TFQA. On the outside, each arc represents the identity of each gene list. On the inside, each arc represents a gene list. The dark orange color represents the genes that are shared by both TCQA and TFQA, and the light orange color represents genes that are unique to each condition. Purple lines link the same genes that are shared by both gene lists. Blue lines link the genes that fall under the same significantly enriched gene ontology term. Common functional networks of TCQA and TFQA using MCODE algorithm. (D) Ras signaling pathway. (E) Muscle structure development. (F) Mitochondrial translation. (G) Regulation of the MAPK cascade. Network nodes are displayed as pies. The color code for the pie sector represents a gene list. The significance threshold was set to P-value <0.05 and FC >1.2.

TFQA Mediates ErbB Signaling to Enhance Jun and Myc, while TCQA Mediates Myc

To find the molecular mechanism activated by TCQA and TFQA treatments, the protein–protein interaction (PPI), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and Kinase Enrichment Analysis 3 (KEA3) analyses were considered. PPI analysis is a fundamental aspect of understanding the behavior of proteins within cells and their roles in various BPs. PPI analysis was performed using RankProd DEGs, which elucidated functional modules between the genes. RankProd is a statistical method to prioritize genes. The interaction PPI network of TCQA contained 1218 nodes, 1603 edges, and 309 seeds (Figure 4A). In the interaction PPI network of TFQA-treated DEGs, there were 1220 nodes, 1658 edges, and 262 seeds. From the PPI network of TCQA and TFQA, the cell cycle, neurotrophin signaling pathway, MAPK signaling pathway, erythroblastic oncogene B (ErbB) signaling pathway, and phosphoinositide-3-kinase (PI3K)-protein kinase B (Akt) signaling pathway were enriched significantly. As part of the upstream signal, the ErbB signaling pathway mediates the mitotic signaling cascade and regulates kinase activity in the PI3K-Akt and MAPK pathways.18 Stimulating ErbB receptors can improve neurogenesis by activating Ca2+ activity in addition to learning and cognitive capabilities in patients with mental disorders.19 Therefore, ErbB signaling can effectively regulate neurogenesis, neuronal activity, and neural repair. Furthermore, using integrated kinase analyses of TCQA- and TFQA-treated samples, the mean rank score is a metric which refers to the average rank of a kinase among a set of potential targets or substrates based on computational prediction or experimental data. The same integrated kinases expressed in TCQA and TFQA were found. Downstream receptors AKT and MAPK kinases were expressed significantly. As important receptors of the ErbB signaling pathway, the epidermal growth factor receptor 1 (EGFR), receptor tyrosine-protein kinase erbB-2 (ERBB2), receptor tyrosine-protein kinase erbB-3 (ERBB3), and receptor tyrosine-protein kinase erbB-4 (ERBB4) were enriched obviously. In previous studies, neural differentiation and neuronal survival are induced by activation of EGFR signaling.20 Heterodimerization of ERBB2 receptors is necessary for neuregulin signaling. ERBB2 plays an important role in normal peripheral nervous system development.21 For the two other ErbB family kinases, ERBB3 and ERBB4 are highly expressed in the postsynaptic membrane.22 Additionally, ERBB4 knockout causes neuronal and behavioral deficits.23 It is demonstrated that ErbB signaling plays a vital role in promoting MAPK and AKT kinases, thereby enhancing neurogenesis in TCQA and TFQA treatments.

Figure 4.

Figure 4

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Functional networks in TCQA and TFQA-treated NSCs.(A) Generic PPI networks of DEGs by TCQA and TFQA and KEGG pathways significantly enriched in PPI networks. Bar graphs showingintegrated kinase enrichments by the DEGs in TCQA and TFQA. (B) Module 0 interaction network of the ErbB signaling pathway extracted with the Walktrap algorithm and enrichment dot bubbles showing key hub nodes in TCQA. (C) Module 0 interaction network of the ErbB signaling pathway extracted with the Walktrap algorithm and enrichment dot bubbles showing key hub nodes in TFQA. Networks were constructed using NetworkAnalyst web tool with DEGs with a P-value <0.05 and FC >1.2. In the module 0 interaction networks, nodes represent proteins. Edges illustrate the first-order interactions between two connecting proteins. Seeds are a subset of nodes used as starting points or reference points for various analyses or computations on the PPI network. Shades of red in nodes illustrate the significance of degrees. The color degree represents topological strength. Blue nodes represent the most significant enriched protein. In the enrichment dot bubbles, bubble sizes refer to betweenness centralities, how often a node lies on the shortest paths between other nodes in a network. The bubble color represents fold enrichments, how much more frequently a particular set of proteins appears in a network compared to what would be expected by chance. The Y-axis refers to the number of degrees, which is the count of direct connections a node has to other nodes in the network. (D) Average signal intensity of Myc- and Jun-top 100 targeted genes in the control and TCQA and TFQA treatments. Red represents a strong signal intensity. Blue represents a weak signal intensity.

At the next stage, we studied the effect on promoting the neurogenesis of TCQA and TFQA in ErbB signaling. The full hub genes’ list of TCQA in the ErbB signaling pathway can be obtained from Tables S1 and S2. The full hub upregulated and downregulated genes’ lists of the ErbB signaling pathway in TFQA can be found in Tables S3 and S4. As shown in Figure 4B, the module 0 interaction network and key hub genes of the ErbB signaling pathway in TCQA were presented. The module 0 interaction network and key hub genes of the ErbB signaling pathway of TFQA are shown (Figure 4C). Module Explore and Walktrap algorithms were considered. Module Explore was designed to identify densely connected subgraphs within a larger network. Walktrap is another community detection algorithm that operates by clustering nodes based on the similarity of their respective walks. Topological strength refers to a metric that quantifies the importance of a node within the network based on its structural position and connectivity to provide a measure of how central or influential a node is in the network topology. In TCQA treatment, the myelocytomatosis oncogene (Myc) had the greatest number of degrees, with a value of 7. The fold enrichment of Myc was 1.53, and the betweenness was 62.01667. Myc is critical for normal neurogenesis, regulating NSC proliferation, differentiation, and nuclear size. The Myc protein drives differentiation by increasing neurogenic cell division, regulating neurogenesis in NSCs before the onset of neuronal differentiation.24Myc appears to control axonal regeneration through the expression of telomerase reverse transcriptase and p53.25 Specially, Myc was also expressed significantly in TFQA treatment with the number of degrees of 6, the betweenness of 29.04444, and the fold enrichment of 1.47. Moreover, the Jun proto-oncogene (Jun) had the greatest number of degrees, with a value of 12, and the most direct connections between nodes in the ErbB signaling pathway of TFQA treatment. The fold enrichment of Jun was 1.98 and the betweenness was 68.03056 in TFQA treatment. Jun may be related to neuroprotection and regeneration in the adult nervous system by axonal sprouting.26 Dysregulation of Jun enzymes leads to many diseases, including neurodegeneration.27 Interestingly, the P-value of Jun was not significant in TCQA treatment because the network is also constructed based on the curated interaction databases like STRING, BioGRID, or IntAct, which include known protein interactions regardless of expression levels. Therefore, although Jun was not significantly expressed in the TCQA treatment, it was also shown in the network. Furthermore, the CD40 molecule (Cd40) was downregulated in TFQA, which has the opposite effects on dendritic growth and elaboration.28

To compare the different regulations of Myc and Jun in TCQA and TFQA, the top 100 most relevant genes of Myc and Jun were screened in Enrichr analysis (Figure 4D). Enrichr is a web-based tool used for gene set enrichment analysis and visualization. The enriched terms and pathways were navigated to identify the top 100 most relevant genes associated with biological processes or pathways of interest. Comparing the average signal intensity of Myc- and Jun-targeted genes, the signal strengths of TCQA and TFQA were in outstanding contrast. Myc proteins, c-, L-, and N-Myc, each have unique roles in directing the growth of brain regions. In NSCs of adult brains, c-Myc overexpression significantly increases proliferation, whereas c-Myc knockdown has the opposite effect of decreasing proliferation.29 L-Myc transcripts are highly expressed in proliferative regions of the brain and neural tube.30 N-Myc regulates cerebellar granule neuron precursors and promotes the neural precursor proliferation.31 It can indicate that Myc is crucial in the self-renewal capability. As the special protein with the highest degree in TFQA, the Jun protein c-Jun is required for efficient axonal regeneration, and c-Jun deficiency causes motor neuron atrophy. c-Jun N-terminal kinase (JNK) activation is involved in the neuronal differentiation of NSCs and the neurite outgrowth of NSC-derived neurons.32 JNK is a critical cellular stress response protein induced by oxidative stress, which plays a major role in susceptible neurons of Alzheimer’s disease.33 Notably, inhibition of JNK and knockdown of JNK can promote the apoptotic pathway. Inhibition of JNK leads to the weakening of the neuroprotective function.34 The remarkable capability of Jun to promote neuronal differentiation was demonstrated. Overall, it is illustrated that TFQA significantly promotes neurogenesis by mediating the differentiation gene Jun as the gene with the most connections and the proliferation gene Myc of the ErbB signaling pathway, while TCQA mediates Myc, which is the most connected gene in ErbB signaling.

ErbB Signaling Pathway Activates Synaptic Growth and Leads to Increased Neurogenesis in NSCs of TCQA and TFQA Treatments

To further explore the degree of gene expression and the possible neural effects between TCQA and TFQA, we created heatmaps summarizing the top upregulated DEGs of TCQA and TFQA, as RankProd results. The proliferation-related gene Ran GTPase activating protein 1 (Rangap1) was upregulated in TCQA, while lysine acetyltransferase 7 (Kat7) was expressed significantly in TFQA (Figure 5A). In DEGs related to neurogenesis, the mechanistic target of rapamycin kinase (Mtor) was stimulated by 2.65 FC of TCQA and 1.66 FC of TFQA (Figure 5B). As a key signaling molecule for NSC differentiation, the SUFU negative regulator of hedgehog signaling (Sufu) was significantly expressed with 2.41 and 2.69 FC, respectively.35 As shown in Figure 5C, the neuronal survival-associated gene SNF-related kinase (Snrk) was upregulated by TFQA treatment. Regarding gliogenesis-related DEGs, the SRY-box transcription factor 8 (Sox8) was upregulated by TCQA treatment (Figure 5D). The cell adhesion molecule 4 (Cadm4) was expressed with 9.64 FC in TFQA. As shown in Figure 5E, the synapse-related gene heterogeneous nuclear ribonucleoprotein M (Hnrnpm) was upregulated, having a significant FC of 2.31 in TCQA and 2.2 in TFQA. Lack of Hnrnpm leads to a decrease in synaptic proteins, thereby disrupting synaptic plasticity and ultimately leading to cognitive impairment.36 Covering neurotransmitter-associated DEGs, the solute carrier family 6 member 8 (Slc6a8) and sestrin 2 (Sesn2) were upregulated effectively in TCQA and TFQA (Figure 5F). In addition, the memory-associated gene transmembrane and coiled-coil domain family 1 (Tmcc1), FC of 2.74 and 3.54 respectively in TCQA and TFQA, was showed in Figure 5G. Finally, related to the neurological disorder, the stimulated G protein-coupled receptor 52 (GPR52) had significant FC values of 6.39 in TCQA and 6.52 in TFQA. (Figure 5H). The coupled receptor GPR52 is expressed exclusively in the brain, primarily in circuits associated with symptoms of neuropsychiatric and cognitive disorders.37 It is further proved that there are significantly different DEGs between TCQA and TFQA treatments, while the top DEGs express the functions of nerve growth and protection.

Figure 5.

Figure 5

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Neural functions by top 100 upregulated DEGs in TCQA and TFQA treated NSCs. Kinases integrated by DEGs and the significant gene seeds of the ErbB signaling pathway from SynGO annotations for BP functions in TCQA and TFQA. (A) Heatmap displaying the NSC proliferation-related DEG expression. (B) Heatmap displaying the neurogenesis-related DEG expression. (C) Heatmap displaying the neuronal survival-related DEG expression. (D) Heatmap displaying the gliogenesis-related DEG expression. (E) Heatmap displaying the synapse-related DEG expression. (F) Heatmap displaying the neurotransmitter-related DEG expression. (G) Heatmap displaying the memory-related DEG expression. (H) Heatmap displaying the neurological disorder-associated DEG expression. Red represents upregulation. Blue represents downregulation. The generic PPI network of genes from SynGO annotations for BP functions. (I) Interaction network of the ErbB signaling pathway showing hub nodes from synaptic genes in TCQA. (J) Interaction network of the ErbB signaling pathway showing hub nodes from synaptic genes in TFQA. NetworkAnalyst with P-value <0.05 and FC >1.2 constructed.

Moreover, synaptogenesis and plasticity are essential during the formation of new neurons.38 To study the effect of the ErbB signaling pathway on the synaptic growth function and thus neuronal differentiation, we first performed Synaptic Gene Ontology (SynGO) analysis and obtained the synapse-related gene lists of TCQA and TFQA and submitted the SynGo gene lists for PPI analysis. SynGO focuses on genes that play crucial roles in the formation, maintenance, and plasticity of synapses. Finally, the interaction networks of the ErbB signaling pathways in synapse genes were obtained. As shown in Figure 5I, presenilin 1 (PSEN1) had the greatest number of degrees in TCQA. PSEN1 regulates synaptic homeostasis, and Alzheimer’s disease-related mutations in PSEN1 can change the site of γ-secretase cleavage, thereby increasing the production of longer and highly fibrillated Aβ, thereby treating Alzheimer’s disease.39 Specially, Mtor further regulates Akt1, which was consistent with the KEA3 analysis result. AKT serine/threonine kinase 1 (AKT1) was considered the most significant kinase in TCQA. In TFQA, the FYN proto-oncogene (FYN) is the most significant node (Figure 5J). Increasing FYN activity sensitizes neurons to Aβ-induced neuronal toxicity and exacerbates the Aβ-related neuronal activity and improves the synaptic function.40 In addition, the postsynaptic density protein 95 (PSD-95) interacts with N-methyl d-aspartate and ErbB receptors, recruits FYN kinase into the complex, and promotes tyrosine phosphorylation of N-methyl-d-aspartate receptor subunits and contributes on synaptic plasticity.41 The signal transducer and activator of transcription 3 (STAT3) were also enriched in the ErbB signaling pathway from the SynGo gene list of TFQA. STAT3 phosphorylation promotes neural differentiation.42PSEN1 was also a significantly expressed protein in TFQA. PSEN1 was a coexpressed node of TCQA and TFQA. Moreover, AKT1 and mitogen-activated protein kinase 1 (MAPK1) were enhanced in the ErbB signaling pathway, which was consistent with the KEA3 analysis result of TFQA treatment. In summary, TCQA and TFQA activate AKT and MAPK kinases by mediating the ErbB signaling pathway, thereby enhancing the synaptic growth function, leading to neuronal differentiation.

TFQA Improves the Gene Expression of NSC Proliferation and Differentiation Obviously Comparing with TCQA

According to the previous microarray results, there was significant neural differentiation and self-renewal capabilities in TCQA and TFQA treatments, so the further quantitative real-time polymerase chain reaction (PCR) assay was performed to verify. Nestin plays an important role in the self-renewal of NSCs.43 NSCs expressing Nestin can induce neurogenesis and regulate neuronal fate.44 In Nestin gene expression, 5 μM 48 h TCQA treatment showed an effective self-renewal capacity of the NSCs (Figure 6A). And in the groups of 1 and 5 μM TFQA treatments for 72 h, Nestin expression increased significantly, with 250.639 and 235.216%. It was shown that TCQA and TFQA could improve the proliferation of NSCs more significantly. Moreover, neuronal growth gene neuronal differentiation 1 (Neurod1) controls the survival and maturation of newborn neurons.45 In the 5 μM TCQA for 48 h treatment group, Neurod1 gene expression increased significantly (Figure 6B). In 1 and 5 μM 72 h TFQA treatment groups, Neurod1 expression upped significantly. These results showed that TCQA and TFQA could form synapses and promote neurogenesis outstandingly. Finally, the effect of oligodendrocyte formation was also considered in TCQA and TFQA treatments. The platelet-derived growth factor receptor α (Pdgfra) is from oligodendrocyte precursors in the CNS.46 Oligodendrocyte precursors participate in the formation of oligospheres, which can further differentiate into neuron-like cells.47 Oligodendrocyte precursors form functional excitatory synapses with neurons and express neuronal precursor markers such as SRY-box transcription factor 2 (Sox2), paired box 6 (Pax6), and doublecortin (DCX), suggesting that OPCs may have the capacity for neuronal differentiation.48 There was no significance for Pdgfra expression in TCQA treatments (Figure 6C). However, Pdgfra gene expression increased significantly in 1 and 5 μM TFQA treatments for 48 and 72 h, where the values were 203.333, 264.33, 285.235, and 345.344%, in order. It was indicated that TFQA had the potential of supporting neurogenesis. Overall, the overall quantitative real-time PCR result verifies that TFQA can promote the proliferation and neural differentiation in NSCs more obviously than TCQA.

Figure 6.

Figure 6

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Effects of TCQA and TFQA treatments on the relative gene expression in NSCs time and dose dependently (n = 3 in each group). (A) Nestin expression. (B) Neurod1 expression. (C) Pdgfra expression. Data are expressed as the mean ± SD of three independent experiments. ****p < 0.0001, ***p < 0.001, **p < 0.01, and *p < 0.05.

In conclusion, we studied the effect on the neurogenesis of TCQA and the compound with a similar structure, TFQA, as a newly formed compound, for the first time in NSCs. The development of new strategies to promote neurogenesis in neurodegenerative diseases is a major therapeutic challenge. As an anti-Alzheimer’s disease antineuroinflammatory drug, cinnamoyl acid and its derivatives improve neuroinflammatory pathways and have the neuroprotective potential in neurodegenerative diseases.49,50 For TCQA and TFQA structures, the branches are located at the 3-, 4-, and 5-position bonds. Compounds with 4-position branches on the benzene ring are more anti-inflammatory and biologically active.51,52 The functional group at the 3-position of the C ring is essential for the activity.53 The new heterocyclic compound synthesized at the 5-position has more potent chemical and biological activities.54 Therefore, the neuroprotective activity of TCQA and TFQA may be mainly based on the cinnamoyl acid functional groups and the 3-, 4-, and 5-position bonds. Our results suggest that like TCQA, treatment with TFQA promotes neural protection by increasing the neurogenesis of NSCs. Importantly, for the first time, we find that TFQA and TCQA have a proneurogenic effect in mice NSCs, which occurs through the activation of ErbB signaling pathways. Interestingly, TCQA and TFQA stimulate AKT and MAPT kinases by activating the ErbB signaling. In TCQA treatment, the proliferation gene Myc was regulated significantly and has the greatest direct relations. In TFQA treatment, not only the differentiation gene Jun was upregulated remarkably and had the most significant connections but Myc was also enriched significantly. In addition, TCQA and TFQA enhance neurogenesis by promoting the synaptic growth. Furthermore, the specific types of Myc and Jun transcription factors influenced should be further studied. In addition, in the previous research, TCQA has been shown to have remarkable antiaging and neurogenesis-promoting effects in in vivo studies.5 And TCQA has antioxidant, antibacterial, neuroprotective, anti-inflammatory, anticancer, antiviral, antidiabetic, and cardiovascular effects in several cell and animal models.55 Regarding the comparison of the neuroprotective effects caused by the structural differences between TCQA and TFQA, it was clarified in the other research that the methyl group has more biological activity. Methyl caffeate can inhibit neuronal damage and reduce neurotoxicity by inhibiting necrosis and apoptosis processes.56 The methyl group is quite important to the activity-induced Ca2+ release, compared to the bromine substituent, chlorine, and iodine.57 The compound with the methyl group had anti-inflammatory activity.58 Antillatoxin featuring seven methyl groups enhances neurite outgrowth in immature neurons.59 It is considered that TFQA, which has three more methyl groups than TCQA, may have the greater possible effect on supporting the neural system in in vivo study. Therefore, we hypothesize that TFQA may also have the potential to be used as drugs that, like TCQA, can promote neurogenesis and therapy neurodegenerative diseases.

Methods

Sample Preparation

Synthesized TCQA and TFQA with 90.3 and 88.8% purity were provided by Dr. Tominaga Kenichi and Masataka Hatanaka from the National Institute of Advanced Industrial Science and Technology (AIST). For the in vitro experiment, TCQA and TFQA were prepared by first dissolving in a small volume of 70% ethanol and then diluted in the cell culture medium.

Isolation and Culture of NSCs

6–8 weeks old adult male ICR mice (Charles River, Japan) were used for the experiment (the Gene Research Center (GRC): 22-387). NSCs were isolated and collected from ICR mice brains using the adult brain dissociation kit (Miltenyi Biotec, Germany), Anti-Prominin-1 MicroBeads (Miltenyi Biotec, Germany), and the autoMACS Pro Separator (Miltenyi Biotec, Germany). The NSCs were cultured in 25 cm2 cell culture flasks (BD Falcon) or in 6-well plates (BD Falcon) with a growth medium KnockOut DMEM/F-12 (1X) (Thermo Fisher Scientific), supplemented with the StemPro neural supplement (Thermo Fisher Scientific) and recombinant human fibroblast growth factor basic (FGFb) (Thermo Fisher Scientific). The NSCs were cultured at 37 °C in a 95% air/5% CO2-humidified Heracell VIOS 160i CO2 incubator (Thermo Fisher Scientific). The medium was changed every 3 days to ensure the cells’ survival.

Neurosphere Assay

An All-in-One fluorescence microscope (KEYENCE, Japan) was used to evaluate the number and size of NSCs. Twelve male ICR mice brains were isolated. The NSCs were cultured in 6-well plates (BD Falcon) at a density of 4 × 104 cells/mL and were incubated at 37 °C for 72 h. NSCs were treated without or with 1, 5, 10, and 20 μM TCQA. After incubation, the number and size of NSCs were counted using a BZ-X800 Analyzer.

RNA Isolation Assay

The NSCs were seeded in 6-well plates (BD Falcon) at the density of 1 × 105 cells/well and were incubated at 37 °C. NSCs were treated with a differentiation medium without or with TCQA and TFQA for 24–72 h. After treatment, NSCs were washed with PBS(−) (Fujifilm, Japan). The total RNA was extracted from NSCs using the ISOGEN kit (Nippon Gene Co., Ltd., Toyama, Japan) following the manufacturer’s instructions, as reported previously.4 The total RNA was quantified and assessed for quality with the NanoDrop One/OneC instrument (Thermo Fisher Scientific).

DNA Microarray Analysis

First, total 100 ng of RNA samples were prepared for determining the RNA quantity. Five μL of RNA was added with First-Strand solution (Affymetrix) to synthesize First-Strand cDNA. Second-Strand Buffer and Enzyme (Affymetrix) were added and incubated for 16 h at 40 °C to prepare ss-cDNA. For labeling, the fragmented ss-cDNA samples and Labeling Master Mix (Affymetrix) were mixed and incubated. The GeneChip MG-430 PM microarray (Affymetrix Inc.) was washed and stained in the GeneAtlas Fluidics Station 400 (Affymetrix). The resulting images were scanned using the GeneAtlas Imaging Station (Affymetrix). Data analysis was performed in Partek Express software (Partek). For further analysis, Metascape, VolcaNoseR, Bioinformatics & Evolutionary Genomics, Bioinformatics, Morpheus, NetworkAnalyst, Kinase Enrichment Analysis version 3, Enrichr, and Synaptic Gene Ontologies were used for analysis. The microarray data set is deposited in the Gene Expression Omnibus (GEO) under Accession Number GSE264538.

Quantitative Real-Time PCR Analysis

Twelve male ICR mice brains were isolated and the NSCs were cultured and treated. The extracted RNAs were used as templates for reverse transcription PCR using a SuperScript III reverse transcription kit (Invitrogen, CA). The TaqMan Universal PCR mix and TaqMan probes specific to Nestin (Mm00450205_m1), Neurod1 (Mm01946604_s1), and Pdgfra (Mm00440701_m1) (Applied Biosystems, CA) were used for quantitative real-time PCR. Quantitative real-time PCR Software 1.3.1 (Applied Biosystems, CA) and Gapdh (Mm99999915_g1) (Applied Biosystems, CA) were used as the endogenous control. All reactions were run in triplicate.

Statistical Analysis

The results were obtained as the mean ± standard deviation (SD). Statistical analysis was performed using GraphPad Prism 6 (GraphPad Software) and Student’s t test for comparing two value sets. P-value < 0.05 was considered statistically significant.

Acknowledgments

TCQA and TFQA were provided by Dr. Tominaga Kenichi and Masataka Hatanaka (AIST). This work was supported by the Japan Science and Technology Agency (JST grant number JPMJPF2017). The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Supporting Information Available

The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acschemneuro.4c00329.

  • The effect of TCQA and TFQA treatments on number of NSCs (Figure S1); GO analysis of TCQA and TFQA treatments in NSCs (Figure S2); summary of the upregulated hub genes of the ErbB signaling pathway by TCQA treatment (Table S1); summary of the downregulated hub genes of the ErbB signaling pathway by TCQA treatment (Table S2); summary of the upregulated hub genes of the ErbB signaling pathway by TFQA treatment (Table S3); and summary of the downregulated hub genes of the ErbB signaling pathway by TFQA treatment (Table S4) (PDF)

Author Contributions

H.L.: conceptualization, investigation, methodology, software, visualization, writing—original draft, writing—review and editing, data curation, and formal analysis. K.S.: conceptualization, investigation, methodology, software, writing—review and editing, and validation. F.F.: conceptualization, software, writing—review and editing, and validation. H.I.: conceptualization, methodology, funding acquisition, project administration, resources, supervision, and writing—review and editing.

The authors declare no competing financial interest.

Supplementary Material

cn4c00329_si_001.pdf (384.6KB, pdf)

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