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Article

Effects of Leaf Extracts from Genetic Resource of Capsicum spp. on Neuroprotection and Anti-Neuroinflammation in HT22 and in BV2 Cells

by
Linsha Dong
1,†,
Bo-Ram Choi
2,†,
Hyo Bong Jeong
3,
Hwan Lee
1,
Zhiming Liu
1,
Dahye Yoon
2,
Hye Eun Lee
3,
Dong-Sung Lee
1,* and
Dae Young Lee
4,*
1
Research Institute of Pharmaceutical Sciences, College of Pharmacy, Chosun University, 309 Pilmun-daero, Dong-gu, Gwangju 61452, Republic of Korea
2
Department of Herbal Crop Research, National Institute of Horticultural and Herbal Science, Rural Development Administration, Eumseong 27709, Republic of Korea
3
Department of Horticultural Crop Research, National Institute of Horticultural and Herbal Science, Rural Development Administration, Wanju 55365, Republic of Korea
4
BK21 FOUR KNU Creative BioResearch Group, School of Life Sciences, Kyungpook National University, Daegu 41566, Republic of Korea
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Plants 2024, 13(19), 2820; https://doi.org/10.3390/plants13192820
Submission received: 23 August 2024 / Revised: 5 October 2024 / Accepted: 7 October 2024 / Published: 8 October 2024
(This article belongs to the Special Issue The Bioactivity of Natural Products and Extracts from Horticultural Plants)
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Abstract

:
To develop functional varieties of Capsicum spp. leaves, 40 genetic resources were collected and extracted with 30% aqueous-fermented ethanol. We investigated the protective effects of extracts from 40 genetic resources of Capsicum spp. on glutamate-induced HT22 and LPS-induced BV2 cells. The results showed that the five extracts exhibited cell-protective activities. We also investigated the anti-inflammatory effects of these five extracts on LPS-induced BV2 cell neuroinflammation and found that 23OM18 exhibited superior anti-inflammatory effects. We further investigated the protective activity and anti-inflammatory mechanisms of 23OM18 in these two cell models. In addition, the profiles of 16 metabolites were compared between the representative accessions and among the five genetic resources using ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). The results showed that 23OM18 protected HT22 cells by inhibiting reactive oxygen species generation and regulating the MAPK-JNK signaling pathway, thereby reducing LPS-induced BV2 cell neuroinflammation by regulating the NF-κB and MAPK signaling pathways. Based on these results, 23OM18 has the potential to be developed as a functional food for the treatment of neurodegenerative diseases.

Graphical Abstract

1. Introduction

Neurodegenerative diseases (NDs) are gradually becoming a major burden on human society, affecting millions of people worldwide. The resulting incidence and mortality rates are major healthcare issues. NDs are a diverse category of complicated illnesses characterized by neuronal loss and the gradual degeneration of several parts of the nervous system. Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, and amyotrophic lateral sclerosis are the main types of NDs [1,2]. NDs have complicated and varied pathophysiologies that often include oxidative stress, mitochondrial dysfunction, impaired metal homeostasis, and neuro-inflammation. The molecular mechanism of neurodegeneration remains unknown and presents a significant challenge in the development of effective therapies [3]. Therefore, our understanding of the molecular underpinnings of the neurodegenerative processes must be improved to help discover therapeutic targets for therapy and prevention.
The identification of innate immune function-related AD risk genes and higher levels of inflammatory markers in patients with AD suggest that neuro-inflammation is a major factor in the pathophysiology of AD [4]. Throughout the central nervous system, microglia, which are resident macrophages of the central nervous system, constitute a vast network that helps maintain homeostasis, monitor pathogens and cell debris, and participate in the response and repair processes. Microglia in NDs help with debris clearing but can also contribute to pathogenesis. Microglial damage may be the basis of NDs [5]. Early inflammation following CNS injury is advantageous for eliminating pathogens and delaying the onset of damage, both of which promote tissue healing and regeneration. However, chronic neuro-inflammation associated with neurological disorders may affect the nervous system. Activated microglia boost their phagocytic activity and release pro-inflammatory mediators, such as nitrogen oxide (NO), reactive oxygen species (ROS), cytokines, and chemokines, in response to pathogenic infections [6]. Activated microglia not only play a role in the defense and removal of pathogens but also lead to harm to the brain tissue and cells. They serve as primary initiators of the inflammatory cascade through an increase in chemokine production and responsiveness.
An imbalance in oxidative stress is the primary cause of neurodegenerative illnesses. Neuronal cells are highly vulnerable to oxidative stress and are likely to produce significant quantities of ROS because of their high oxygen consumption [7,8]. Glutamate is the primary mediator of the excessive excitatory neurotransmission induced by excitatory toxicity in neurons. In the hippocampal region, elevated levels of extracellular glutamate stimulate N-methyl-d-aspartate receptors, facilitating the uptake of Ca2+ into neuronal cells. Increased intracellular Ca2+ levels cause ROS generation, and when these ROS accumulate, they can oxidize proteins, lipids, and DNA, causing damage to cells [9].
Capsicum spp., commonly known as chili peppers, belong to the family Solanaceae. Dried chili pepper has been used in the human diet as an important spice and source of nutrients. Capsicum spp. are also used as raw materials in several traditional drug therapies. The fruits of Capsicum spp. have been used to cure dyspepsia, appetite, and flatulence, as well as to enhance digestion and circulation. They have also been used as tonics and antibacterial and stimulatory agents [10]. Chili peppers are nutritious, functional foods that contain numerous healthy chemicals, including carotenoids, anthocyanins, flavonoids, phenolic compounds, capsaicin, and various vitamins and minerals [11]. However, the health benefits of chili peppers on degenerative diseases have not yet been studied. In this study, 40 genetic resources were collected, including those with high alpha-glucosidase inhibitory (AGI) activity and high content of major flavonoid components. We investigated the protective effects of extracts from 40 genetic resources of Capsicum spp. on glutamate-induced HT22 and LPS-induced BV2 cells. The results have potential applications in various industries, including food, nutraceuticals, and pharmaceuticals.

2. Results

2.1. Passport Data of 40 Generic Resources from Capsicum spp.

Information regarding the source of introduction and the species name of each genetic resource is summarized in Table 1. Most accessions belonged to the cultivated species Capsicum annuum; however, some resources belonged to other species with different morphological and physiological characteristics. Table 2 shows the key morphological characteristics of the genetic resources, including the plant height and leaf length. The average plant height of the genetic resources was 73.0 cm, and the average leaf length was 11.9 cm. 23OM18 was taller than average, but the length of the leaves was similar.

2.2. Effects of Leaf Samples of the 40 Genetic Resources from Capsicum spp. Extracts on Glutamate-Induced Oxidative Stress in HT22 Cells

To explore whether these 40 extracts have neuroprotective effects, we used a glutamate-induced HT22 cell model to screen all the extracts. Among these 40 extracts, 5 extracts (23OM16, 23OM17, 23OM18, 23OM19, and 23OM20) showed significant protective effects against glutamate-induced cell death (Figure 1). The cell protection values (EC50) are shown in Table 3. Of these, 23OM18 exhibited the highest protective activity with an EC50 value of 102.6 ± 0.2934 μg/mL.

2.3. Effects of 23OM18 on ROS Production in HT22 Cells

After stimulation with glutamate for 8 h, we examined ROS production in HT22 cells using DCFH-DA and photographed them under a fluorescence microscope. Due to the lack of protective effect at 50 μg/mL, we performed the ROS experiment only at 100 and 200 μg/mL concentrations of 23OM18. As shown in Figure 2B,C, 23OM18 at concentrations of 100 and 200 μg/mL significantly reduced ROS generation.

2.4. Effects of 23OM18 on the MAPK Signaling Pathway in HT22 Cells

To explore the mechanism by which 23OM18 exerts its protective effect, we examined the effect of 23OM18 on the MAPK signaling pathway. We found that 23OM18 inhibited JNK phosphorylation. The results are shown in Figure 3 A,B. In the MAPK pathway, p38 and ERK levels were not affected by 23OM18.

2.5. Effects of 23OM18 on LPS-Induced Cytokine Secretion in BV2 Cells

In previous experiments, we found that 23OM18 has a neuroprotective effect on hippocampal neuronal cells. We explored the effects of 23OM18 on LPS-induced BV2 cells. BV2 cells were pre-treated with 23OM18 for 3 h and then stimulated with LPS for 24 h. The levels of pro-inflammatory factors in the cell supernatants were then determined. The results are shown in Figure 4. The levels of nitrite, TNF-α, IL-6, and PGE2 were significantly increased by LPS. The 23OM18-treated group exhibited inhibitory effects on these pro-inflammatory mediators.

2.6. Effects of 23OM18 on iNOS and COX-2 Expression in LPS-Induced BV2 Cells

The expression of inducible nitric oxide synthase (iNOS), the enzyme that catalyzes the production of NO from L-arginine, is frequently associated with inflammatory and malignant diseases. The expression of iNOS was significantly increased by LPS. As shown in Figure 5A,B, pre-treatment with 23OM18 inhibited iNOS expression. Another enzyme that plays an important role in inflammation is COX-2. COX-2 catalyzes the rate-limiting step in the conversion of arachidonic acid into prostaglandins. The initial inflammatory response to injury or infection is strongly induced by COX-2, which is seldom detectable under normal physiological conditions. In our results, 23OM18 also decreased the expression of COX-2. The results are shown in Figure 5A,B. 23OM18 has a significant inhibitory effect on the expression of iNOS and COX-2. It also exerts anti-inflammatory effects.

2.7. Effects of 23OM18 on the NF-κB Signaling Pathway in LPS-Induced BV2 Cells

NF-κB signaling is critical for immune responses. Normally, NF-κB forms a complex with inhibitory IκB proteins in the cytoplasm, where it is sequestered in an inactive state. These signals, which are triggered by stimuli, target NF-κB complexes and translocate them to the nucleus, where they control gene transcription. We examined the regulatory effects of 23OM18 on the NF-κB signaling pathway. As shown in Figure 6A,B, the transfer of NF-κB (p65) into the nucleus caused by LPS stimulation was significantly inhibited by 23OM18, which also showed an inhibitory effect on the phosphorylation of IκBα and inhibited the decrease in IκBα expression.
Immunofluorescence for p65 is shown in Figure 6C. The translocation of p65 into the nucleus, induced by LPS, was significantly inhibited by 23OM18. Thus, 23OM18 has a significant regulatory effect on the LPS-induced activation of the NF-κB signaling pathway.

2.8. Effects of 23OM18 on the MAPK Signaling Pathway in LPS-Induced BV2 Cells

The process of inflammatory activation usually involves more than one signaling pathway. After being phosphorylated, MAPKs proceed to phosphorylate and activate transcription factors located in the nucleus or cytoplasm, which results in the activation of target genes and thus initiates a range of biological reactions. Western blot results are shown in Figure 7A,B. 23OM18 had a significant inhibitory effect on the expression of phosphorylated ERK and p38 but had no effect on phosphorylated JNK. These results indicate that 23OM18 has a regulatory effect on the MAPK signaling pathway.

2.9. Effects of 23OM18 on LPS-Induced BV2 Cells Co-Cultured with HT22 Cells

To develop an in vitro neuro-inflammation model by establishing a microglia–neuron co-culture system, BV2 microglia were seeded into the upper chamber of the trans-well plate, and HT22 cells were seeded into the lower chamber to establish a BV2-HT22 cell co-culture system. BV2 cells in the upper chamber were stimulated with LPS, and their effect on HT22 neurons in the lower chamber was observed. As shown in Figure 8A, LPS-induced BV2 cells caused the partial death of HT22 cells in the lower chamber, while 23OM18 exerted a protective effect on the HT22 cells. TUNEL staining was performed on HT22 cells, and red-positive cells were observed (Figure 8B,C). This indicated that excessive neuro-inflammation can cause neuronal apoptosis in the BV2-HT22 co-culture system. 23OM18 also plays a role in protecting neurons in co-culture systems.

2.10. Secondary Metabolite Profiling of 23OM16–23OM20

To compare the five extracts (23OM16–23OM20) that showed significant protective effects against glutamate-induced cell death, secondary metabolite profiling was performed using UPLC-QTOF/MS. Table 4 presents the results of the study. Flavonoids such as apigenin and luteolin, organic acids such as citric acid and quinic acid, and capsianoside were detected. Interestingly, capsianosides 1 and 2 were detected at higher levels in 23OM18, which showed the best protective activity compared to other extracts. These results suggested that capsianoside and its derivatives may be involved in the protective activity of 23OM18.

3. Discussion

Oxidative stress (OS) is a critical factor in the development of various pathophysiological conditions. ROS and reactive nitrogen species (RNS) are associated with oxidative stress. They are involved in signaling and preserving physiological homeostasis at appropriate levels [12,13]. These substances are highly destructive to biological molecules, damage DNA, proteins, and lipids, and are often associated with various diseases, including cancer, inflammation, and NDs [14]. Glutamate is the primary mediator of excitatory neurotransmission in the brain [15]. In the nervous system, glutamate is associated with key aspects of normal brain function, including synaptogenesis, learning, cognition, and memory. High glutamate concentrations can induce excessive neuronal depolarization and calcium influx in some illnesses, which can result in oxidative stress, mitochondrial instability, and activation of pathways that ultimately lead to cell death [16]. High amounts of extracellular glutamate deplete intracellular cystine and glutathione, which inhibits cystine absorption into cells via the cystine/glutamate antiporter system and is the mechanism underlying oxidative glutamate toxicity. Oxidative stress is caused by an excessive build-up of reactive oxygen species (ROS) as a result of glutathione depletion [17]. HT22 cells are well-known mouse-derived hippocampal cells. BV2 cells, as microglia, are recognized for their role in regulating neuro-inflammation. Therefore, we aimed to investigate the protective effects in an oxidative damage model induced by glutamate in HT22 hippocampal cells and the modulatory effects on neurodegenerative diseases in BV2 microglia using a neuro-inflammation model induced by LPS in this study. Initially, we evaluated the cytotoxicity of all 40 extracts by treating HT22 cells with concentrations up to 200 µg/mL. As a result, 23OM10 and 23OM30 exhibited cytotoxicity at the highest concentration of 200 µg/mL, whereas all other extracts showed no cytotoxicity at concentrations up to 200 µg/mL. In addition, 23OM18 showed the highest significantly protective effects against glutamate-treated HT22 cells. ROS fluorescence results indicated that the green fluorescence of ROS in HT22 cells pre-treated with 23OM18 was significantly weakened.
MAPK is a kinase cascade that plays an important role in the cellular responses to oxidative stress and inflammation. They can activate MAPK through multiple mechanisms: ROS are directly activated, calcium ions flow into the cells, and free radicals directly oxidize the enzymes in the pathway. ERK is an extracellular kinase that plays a role in cell proliferation, differentiation, and survival. JNK is a c-Jun N-terminal kinase that plays an important role in apoptosis and inflammation. p38 kinase plays a role in cell survival, inflammation, and oxidative stress responses [18,19]. In LPS-induced BV2 cells and glutamate-induced HT22 cells, we detected the regulatory effects of 23OM18 on the MAPK signaling pathway. In HT22 neurons, 23OM18 inhibited glutamate-induced phosphorylation of JNK. Simultaneously, in BV2 microglia, 23OM18 inhibited the phosphorylation of ERK and p38. This evidence indicates that 23OM18 can regulate the MAPK signaling pathway, which may be the basis for its anti-inflammatory and neuroprotective effects.
Increasing evidence supports the fundamental role of neuro-inflammation in the development of NDs. Pro-inflammatory cytokines play a major role in triggering inflammatory responses in the brain [20]. Overactivated microglia will undergo significant changes in phenotype and morphology, accompanied by increased expression of the pro-inflammatory cytokines TNFα, IL-6, IL-1β, and NO. This aggressive state of microglia leads to the formation of a chronic neuro-inflammatory environment and exacerbates neuronal and synaptic loss [21]. In the present study, we detected representative pro-inflammatory cytokines in the activated microglia, such as nitrite, TNF-α, IL-6, and PGE2. These factors play distinct roles in inflammation development. Excessive production of TNF-α can induce inflammatory genes, cell death, endothelial upregulation, recruitment, and the activation of immune cells [22]. As a soluble mediator, IL-6 exerts pleiotropic effects on immunological responses, hematopoiesis, and inflammation. Continued dysregulation of IL-6 production leads to the development of various diseases [23]. When pro-inflammatory cytokines or bacterial products induce immune or epithelial cells, induced NOS (iNOS) is produced. After expression, iNOS continues to generate a large amount of NO for a long time. Higher quantities of NO and its by-products can be harmful to organisms in a number of ways, including blocking important enzymes required for respiration and reproduction [24]. Prostaglandin E2, one of the most prevalent prostaglandins in the body, is connected to a number of inflammatory and immunological processes. It increases vascular permeability and enhances edema and leukocyte infiltration. 23OM18 inhibits the release of these pro-inflammatory factors in LPS-induced microglia, which may be the basis for 23OM18’s regulatory effect on neuro-inflammation.
A bidirectional conversation exists between neurons and microglia in the internal environment of the brain, which is important for steady-state function and is linked to NDs that impair cognitive function [25]. Sustained microglial activation triggers a chronic neuro-inflammatory response that disrupts neuronal health and communication between neurons and microglia [26]. In this study, we established an in vitro co-culture model of hippocampal neurons (HT22) and microglia (BV2) to evaluate the effects of 23OM18 on LPS-induced signaling pathways in microglia and cell viability of hippocampal neurons. Partial apoptosis of HT22 neuronal cells was observed when they were co-cultured with LPS-induced BV2 microglia. 23OM18 exerted a protective effect against HT22 cells. These results indicate that C. annuum can exert neuroprotective effects by regulating neuro-inflammation in microglia and reducing neuro-inflammatory damage to neurons.
Secondary metabolite analysis of C. annuum leaves showed high protective activity, and various compounds such as flavonoids, organic acids, and capsianoside were detected. Among them, higher contents of capsicnoside II and the new capsianoside III were detected in 23OM18, which exhibited the best protective activity. The capsianoside group is an acyclic diterpene glycoside specific to the genus Capsicum. It is classified among monomeric diterpene glycosides, including capsianosides I–XVII, or dimeric esters, including capsianosides A–L [27]. Most of these are found in fruits but have also been reported to be detected or derived from the leaves of the Capsicum genus [28,29].
Although not identified in the secondary metabolite analysis of our study, capsaicin, known as the main component in peppers, is called a capsaicinoid along with dihydro-capsaicin, nordihydrocapsaicin, homodihydrocapsaicin, and homocapsaicin [30]. A study has reported that capsaicin attenuates ROS production in BV2 cells treated with apolipoprotein E, which is known as a genetic risk factor for neurodegenerative diseases [31]. In addition, in a previous study using pepper seed extract, intracellular ROS production in HT22 cells was markedly attenuated with pre-treatment of pepper extract. Luteolin is the bioactive compound in C. annuum corresponding to its anti-neuroexcitotoxic effects, and its potential mechanism may involve improving ROS-mediated cell death. However, capsaicin did not show a significant pharmacological effect against neuroexcitotoxicity [32]. In addition, while the majority of previous studies suggest that C. annuum and its bioactive compounds are generally safe, prolonged or high-dose exposure has been shown to cause significant mucosal irritation. The primary active compound in C. annuum, capsaicin, has reported oral LD50 values of 161.2 mg/kg in rats and 118.8 mg/kg in mice in in vivo models [33].
Excessive ROS cause neuro-oxidative stress, so excessive ROS are associated with a decline in cognitive function [34]. Excessive accumulation of ROS leads to cell death, and the cytoprotective effect in the hippocampal cell line HT-22 is also mainly due to its protective effects against ROS [35]. Additionally, ROS increase the expression of pro-inflammatory genes and promotes the formation and induction of neurotoxicity through lipid peroxidation [36]. In a previous study on capsianosides, compounds isolated from red pepper paste were found to inhibit the formation of CE-OOH, a cholesteryl ester hydroperoxide produced by copper ion-induced oxidation. These compounds were identified as capsianosides F and XVIII, and both showed antioxidant activity by inhibiting CE-OOH formation [37]. In another study, capsianoside V showed the highest DPPH radical activity among the compounds isolated from Murraya koenigii [38]. In a previous study using hot peppers, six compounds were isolated, two of which were confirmed to be members of the capsianoside family. These compounds exhibit inhibitory activity against lipid peroxidation [39]. Additionally, these compounds inhibited COX-1 expression by more than 70%. COX-1 causes cognitive deficits and is associated with neuro-inflammation and neuronal death [40]. Based on the results of previous studies, the superior protective activity of 23OM-18 was assumed to be due to its antioxidant activity against ROS.
Nonetheless, we acknowledge that this study has several limitations. First, additional efficacy validation and mechanistic studies are necessary using in vivo models. Furthermore, it is crucial to elucidate the factors contributing to the differences in efficacy among species, as well as to conduct an analysis of the major components present in the most effective extract, 23OM18. We plan to investigate these aspects in future research.

4. Materials and Methods

4.1. Chemicals and Reagents

Cell culture reagents were purchased from Gibco (Grand Island, NY, USA), and ELISA kits were purchased from BioLegend (San Diego, CA, USA). Primary and secondary antibodies were purchased from Cell Signaling Technology (Danvers, MA, USA). The TUNEL Red Staining Kit was purchased from ROCHE (Basel, Switzerland). All other reagents were purchased from Sigma-Aldrich (St. Louis, MO, USA).

4.2. Plant Materials and Extractions

Forty pepper species, including Capsicum annuum, C. chinense, and C. frutescens, were used in this study (Table 1). Most accessions were C. annuum, comprising 35 accessions. Their taxonomical information was referenced in the database provided by the National Institute of Agricultural Sciences (NIAS, Jeonju, Republic of Korea) Genebank, the national genetic resources control tower. Along with species information, several key horticultural characteristics corresponding to the voucher can be obtained based on the introduction (IT) number in the Genebank. Species name of accessions without IT numbers were identified based on morphological and genetic characteristics according to previous studies [41]. Seeds of 33 accessions were obtained from the National Institute of Horticultural and Herbal Science (NIHHS, Wanju, Republic of Korea), 11 of which were first introduced to the Genebank. Seeds of the remaining seven cultivars were obtained from the respective seed companies. Accessions up to number 20 were selected based on a previous study on flavonoid metabolite profiling [42]. Seeds were sown on 22 February 2023, in plastic trays (Heungnong, Seoul, Republic of Korea) filled with coco peat-containing bed soil. On 25 April 2023, fully grown 60-day-old seedlings were transferred to a greenhouse using a randomized complete block design. The soil pH and EC were 7.0 and 2.5 dS/m, respectively. The plants were watered regularly using a drip irrigation system and fertilized weekly with a nutrient solution (Daeyu, Seoul, Republic of Korea). At 45 days after transplantation, when the plants were 70 cm tall on average, the fully developed leaves around the buds were harvested for further analysis (Table 2).
The harvested leaves were lyophilized to eliminate residual water and then homogenized. The powdered leaves were extracted with 30% aqueous fermented ethanol under reflux conditions at 70 °C for 4 h, and the residue was subsequently re-extracted under the same conditions. The combined filtrates from the primary and secondary extractions were completely desiccated using a rotary evaporator and used for subsequent experiments.

4.3. Cell Culture

HT22 cells were cultured in Dulbecco’s modified Eagle medium (DMEM) (10% FBS), and BV2 cells were cultured in RPMI-1640 medium (10% FBS) under 5% CO2 and 37 °C.

4.4. ROS Staining

HT22 cells were seeded at a density of 1 × 105 cells/mL in 6-well plates. The cells were pre-treated with 23OM18 at a concentration of 100–200 μg/mL for 3 h. The cells were then stimulated with glutamate (5 μM) for 8 h, the culture medium was discarded, and the cells were washed twice with PBS. The cells were then co-incubated with 10 μM DCFH-DA (FBS-free medium) for 30 min. The cells were washed twice with PBS and photographed under a fluorescence microscope at excitation and emission wavelengths of 488 and 525 nm, respectively.

4.5. Western Blot

The harvested cells were lysed with RIPA buffer (St. Louis, MO, USA). To detect the protein concentration, the cells were mixed with the sample buffer for denaturation, followed by SDS-PAGE gel electrophoresis, and then transferred to a nitrocellulose membrane. The membrane was blocked with 5% skim milk (in TBST) for 1 h in room temperature, and incubated with specific primary (1:1000 in 3% skim milk in TBST) overnight at 4 °C, then washed with TBST for 3 times in 30 min, incubated with secondary antibodies (1:5000 in 1% skim milk in TBST) for 1 h in room temperature, washed with TBST for 3 times in 30 min, developed with ECL solution, and photographed.

4.6. Nitrite Detection and ELISA

The BV2 cells were seeded at a density of 5 × 104 cells/mL in a 24-well plate. The cells were pre-treated with 100–200 μg/mL 23OM18 for 3 h and then stimulated with LPS (0.5 μg/mL) for 24 h. The cell culture supernatant was preserved. Nitrite detection was performed using the Griess reagent (St. Louis, MO, USA). Griess mixture was mixed with the same volume of the cell supernatant, and absorbance was measured at 570 nM. IL-6, TNF-α, and PGE2 were detected using the ELISA kit with the cell supernatant, following the manufacturer’s instructions.

4.7. Protein Extraction

For NF-κB, nuclear and cytoplasmic protein extraction was performed according to the manufacturer’s instructions.

4.8. Immunofluorescence

To assess NF-κB (p65) translocation to the nucleus, the BV2 cells were seeded on a round glass slide. The cells were pre-treated with 23OM18 (200 μg/mL) for 3 h and then stimulated with LPS for 15 min. The cells were fixed, solubilized, blocked, incubated with primary antibodies, and then incubated with FITC-linked secondary antibodies. The slides were mounted using an anti-fade mounting medium and photographed under a fluorescence microscope.

4.9. BV2-HT22 Co-Culture System

BV2 cells were seeded at a density of 5 × 104 cells/mL in a 24-well plate with a trans-well insert (0.4 μm) in each well above the HT22 cells. The cells were co-cultured for 24 h, pre-treated with 23OM18 (100–200 μg/mL) for 3 h, and then stimulated LPS (0.5 μg/mL) for 24 h. MTT (5 mg/mL) was added to the HT22 culture medium for 1 h, and DMSO was used to dissolve the formazan crystals. The absorbance was read at 540 nm.

4.10. TUNEL Red Staining

After stimulation with LPS for 24 h in the BV2-HT22 co-culture system, HT22 cells were used to check for in situ cell death (TUNEL kit), following the manufacturer’s instructions.

4.11. Statistical Analysis

Data are presented as the mean ± standard deviation (SD). One-way analysis of variance (ANOVA) followed by Tukey’s post hoc test was performed using GraphPad Prism software (version 8.0). Statistical significance was set at * p < 0.05, ** p < 0.01, and *** p < 0.001. Each experiment was repeated thrice.

4.12. Metabolomic Analysis of Plant Extracts Using UPLC-QTOF/MS

For the ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF/MS) analysis, 100 mg of fine powder was weighed, suspended in 1 mL of solvent (70% MeOH), and ultrasonically extracted for 30 min at room temperature. The supernatant was obtained from samples by centrifugation (13,500× g, 5 min at 4 °C). All samples were diluted 20 times and filtered through a syringe filter (PTFE, 0.2 µm). UPLC-QTOF/MS analysis was performed using an ACQUITY-H-Class UPLC system (Waters Corp., Milford, MA, USA). Separation was performed using an Acquity BEH C18 column (2.1 mm × 100 mm; 1.7 um). The column was maintained at 25 °C, whereas the auto sampler was set at 10 °C. The mobile phase consisted of a combination of solvent A (water containing 0.1% formic acid (v/v)) and solvent B (acetonitrile containing 0.1% formic acid (v/v)) at a flow rate of 0.4 mL/min. The elution conditions were as follows: 0–4 min, B 10–30%; 4–7 min, B 30–35%; 7–9 min, B maintains 35%; 9–12 min, B 35–40%; 12–15 min, B 40–85%; 15–18 min, B 85–10%. MS analysis was conducted using a Waters Xevo G2-S QTOF MS (Waters Corp.) in the negative ion mode. The MS data were acquired in the MSE acquisition mode, which performs alternate high- and low-energy scans. The operating MS parameters were set as follows: source temperature: 120 °C, desolvation temperature: 550 °C, cone gas flow: 30 L/h, gas flow: 800 L/h, capillary voltage: 2.2 kV, cone voltage: 40 V. Leucine encephalin (m/z 554.262) was infused during data acquisition as an internal reference to obtain accurate mass measurements.

5. Conclusions

NDs are major health issues in the elderly population. We investigated the effects of Capsicum spp. leaf samples, obtained from 40 genetic resources from Capsicum spp., on NDs. The experimental results indicate that the leaves of the pepper variety 23OM18 (Uiryeonggabeul) exhibit inhibitory effects on neuro-inflammation in microglia and protective effects on hippocampal neurons. C. annuum leaves can be eaten raw, used to make salads, or used to make various dishes containing meat. Thus, this plant has the potential to be used as a functional food for regulating NDs.

Author Contributions

L.D.: Data curation, investigation, methodology, validation, writing—original draft, and writing—review and editing. B.-R.C.: Data curation, investigation, methodology, and writing—original draft. H.B.J.: Resources, investigation, and writing—original draft. H.L.: Data curation, and investigation. Z.L.: Data curation, and investigation. D.Y.: Data curation, and investigation. H.E.L.: Resources, conceptualization, funding acquisition, and project administration. D.-S.L.: Conceptualization, funding acquisition, project administration, supervision, writing—original draft, and writing—review and editing. D.Y.L.: Conceptualization, funding acquisition, project administration, supervision, writing—original draft, and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by the “Cooperative Research Program for Agriculture Science and Technology Development” (Project No. RS-2023-00218344) of the Rural Development Administration, Republic of Korea. This study was supported by the 2024 RDA Fellowship Program of the National Institute of Horticultural and Herbal Science, Rural Development Administration, Republic of Korea.

Data Availability Statement

The data are contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Armstrong, R. What causes neurodegenerative disease? Folia Neuropathol. 2020, 58, 93–112. [Google Scholar] [CrossRef]
  2. Gitler, A.D.; Dhillon, P.; Shorter, J. Neurodegenerative disease: Models, mechanisms, and a new hope. Dis. Model. Mech. 2017, 10, 499–502. [Google Scholar] [CrossRef]
  3. Chou, S.-C.; Aggarwal, A.; Dawson, V.L.; Dawson, T.M.; Kam, T.-I. Recent advances in preventing neurodegenerative diseases. Fac. Rev. 2021, 10, 81. [Google Scholar] [CrossRef]
  4. Calsolaro, V.; Edison, P. Neuroinflammation in Alzheimer’s disease: Current evidence and future directions. Alzheimers Dement. 2016, 12, 719–773. [Google Scholar] [CrossRef]
  5. Kwon, H.S.; Koh, S.H. Neuroinflammation in neurodegenerative disorders: The roles of microglia and astrocytes. Transl. Neurodegener. 2020, 9, 42. [Google Scholar] [CrossRef]
  6. Tanaka, T.; Narazaki, M.; Kishimoto, T. IL-6 in inflammation, immunity, and disease. Cold. Spring Harb. Perspect. Biol. 2014, 6, a016295. [Google Scholar] [CrossRef]
  7. Sies, H.; Belousov, V.V.; Chandel, N.S.; Davies, M.J.; Jones, D.P.; Mann, G.E.; Murphy, M.P.; Yamamoto, M.; Winterbourn, C. Defining roles of specific reactive oxygen species (ROS) in cell biology and physiology. Nat. Rev. Mol. Cell Biol. 2022, 23, 499–515. [Google Scholar] [CrossRef]
  8. Dumas, A.; Knaus, U.G. Raising the ‘good’oxidants for immune protection. Front. Immunol. 2021, 12, 698042. [Google Scholar] [CrossRef]
  9. Sears SM, S.; Hewett, S.J. Influence of glutamate and GABA transport on brain excitatory/inhibitory balance. Exp. Biol. Med. 2021, 246, 1069–1083. [Google Scholar] [CrossRef]
  10. Villa-Rivera, M.G.; Ochoa-Alejo, N. Chili pepper carotenoids: Nutraceutical properties and mechanisms of action. Molecules 2020, 25, 5573. [Google Scholar] [CrossRef]
  11. Varghese, S.; Kubatka, P.; Rodrigo, L.; Gazdikova, K.; Caprnda, M.; Fedotova, J.; Zulli, A.; Kruzliak, P.; Büsselberg, D. Chili pepper as a body weight-loss food. Int. J. Food Sci. Nutr. 2017, 68, 392–401. [Google Scholar] [CrossRef]
  12. Gu, S.; Li, Y.; Jiang, Y.; Huang, J.H.; Wang, F. Glymphatic dysfunction induced oxidative stress and neuro-inflammation in major depression disorders. Antioxidants 2022, 11, 2296. [Google Scholar] [CrossRef]
  13. Mullen, L.; Mengozzi, M.; Hanschmann, E.-M.; Alberts, B.; Ghezzi, P. How the redox state regulates immunity. Free Radic. Biol. Med. 2020, 157, 3–14. [Google Scholar] [CrossRef]
  14. Rummel, N.G.; Butterfield, D.A. Altered metabolism in Alzheimer disease brain: Role of oxidative stress. Antioxid Redox Signal. 2022, 36, 1289–1305. [Google Scholar] [CrossRef]
  15. Cassano, T.; Pace, L.; Bedse, G.; Michele Lavecchia, A.; De Marco, F.; Gaetani, S.; Serviddio, G. Glutamate and mitochondria: Two prominent players in the oxidative stress-induced neurodegeneration. Curr. Alzheimer Res. 2016, 13, 185–197. [Google Scholar] [CrossRef]
  16. Sabogal-Guáqueta, A.M.; Hobbie, F.; Keerthi, A.; Oun, A.; Kortholt, A.; Boddeke, E.; Dolga, A. Linalool attenuates oxidative stress and mitochondrial dysfunction mediated by glutamate and NMDA toxicity. Biomed. Pharmacother. 2019, 118, 109295. [Google Scholar] [CrossRef]
  17. Khatri, N.; Thakur, M.; Pareek, V.; Kumar, S.; Sharma, S.; Datusalia, A.K. Oxidative stress: Major threat in traumatic brain injury. CNS Neurol. Disord. Drug Targets 2018, 17, 689–695. [Google Scholar] [CrossRef]
  18. Wang, X.X.; Zhang, B.; Xia, R.; Jia, Q.Y. Inflammation, apoptosis and autophagy as critical players in vascular dementia. Eur. Rev. Med. Pharmacol. Sci. 2020, 24, 18. [Google Scholar]
  19. Valipour, M.; Mohammadi, M.; Valipour, H. CNS-Active p38α MAPK Inhibitors for the Management of Neuroinflammatory Diseases: Medicinal Chemical Properties and Therapeutic Capabilities. Mol. Neurobiol. 2024, 61, 3911–3933. [Google Scholar] [CrossRef]
  20. Smith, J.A.; Das, A.; Ray, S.K.; Banik, N.L. Role of pro-inflammatory cytokines released from microglia in neurodegenerative diseases. Brain Res. Bull. 2012, 87, 10–20. [Google Scholar] [CrossRef]
  21. Navaei-Alipour, N.; Mastali, M.; Ferns, G.A.; Saberi-Karimian, M.; Ghayour-Mobarhan, M. The effects of honey on pro-and anti-inflammatory cytokines: A narrative review. Phytother. Res. 2021, 35, 3690–3701. [Google Scholar] [CrossRef]
  22. Kalliolias, G.D.; Ivashkiv, L.B. TNF biology, pathogenic mechanisms and emerging therapeutic strategies. Nat. Rev. Rheumatol. 2016, 12, 49–62. [Google Scholar] [CrossRef]
  23. Nam, K.N.; Woo, B.C.; Moon, S.K.; Park, S.U.; Park, J.Y.; Hwang, J.W.; Bae, H.S.; Ko, C.N.; Lee, E.H. Paeonol attenuates inflammation-mediated neurotoxicity and microglial activation. Neural Regen. Res. 2013, 8, 1637–1643. [Google Scholar]
  24. Waltz, P.; Escobar, D.; Botero, A.M.; Zuckerbraun, B.S. Nitrate/nitrite as critical mediators to limit oxidative injury and inflammation. Antioxid. Redox Signal. 2015, 23, 328–339. [Google Scholar] [CrossRef]
  25. Nam, K.N.; Kim, K.P.; Cho, K.H.; Jung, W.S.; Park, J.M.; Cho, S.Y.; Park, S.K.; Park, T.H.; Kim, Y.S.; Lee, E.H. Prevention of inflammation-mediated neurotoxicity by butylidenephthalide and its role in microglial activation. Cell. Biochem. Funct. 2013, 31, 707–712. [Google Scholar] [CrossRef]
  26. Marinelli, S.; Basilico, B.; Marrone, M.C.; Ragozzino, D. Microglia-neuron crosstalk: Signaling mechanism and control of synaptic transmission/Seminars in cell & developmental biology. Semin. Cell Dev. Biol. 2019, 94, 138–151. [Google Scholar]
  27. Schulz, M.; Hubner, F.; Humpf, H.U. Evaluation of Food Intake Biomarkers for Red Bell Peppers in Human Urine Based on HPLC-MS/MS Analysis. Mol. Nutr. Food Res. 2024, 68, 2300464. [Google Scholar] [CrossRef]
  28. Yahara, S.; Kobayashi, N.; Izumitani, Y.; Nohara, T. New Acylic Diterpene Glycosides, Capsianosides VI, G and H from the Leaves and Stems of Capsicum annuum L. Chem. Pharm. Bull. 1991, 39, 3258–3260. [Google Scholar] [CrossRef]
  29. Barrajon-Catalan, E.; Álvarez-Martínez, F.J.; Borras, F.; Perez, D.; Herrero, N.; Ruiz, J.J.; Micol, V. Metabolomic analysis of the effects of a commercial complex bio stimulant on pepper crops. Food Chem. 2020, 310, 125818. [Google Scholar] [CrossRef]
  30. Batiha, G.E.; Alqahtani, A.; Ojo, O.A.; Shaheen, H.M.; Wasef, L.; Elzeiny, M.; Ismail, M.; Shalaby, M.; Murata, T.; Zaragoza-Bastida, A.; et al. Biological Properties, Bioactive Constituents, and Pharmacokinetics of Some Capsicum spp. and Capsaicinoids. Int. J. Mol. Sci. 2020, 21, 5179. [Google Scholar] [CrossRef]
  31. Wang, C.; Lu, J.; Sha, X.; Qiu, Y.; Chen, H.; Yu, Z. TRPV1 regulates ApoE4-disrupted intracellular lipid homeostasis and decreases synaptic phago-cytosis by microglia. Exp. Mol. Med. 2023, 55, 347–363. [Google Scholar] [CrossRef] [PubMed]
  32. Kang, J.Y.; Gu, J.Y.; Baek, D.C.; Son, C.G.; Lee, J.S. A Capsicum annuum L. seed extract exerts anti-neuroexcitotoxicity in HT22 hippocampal neurons. Food Funct. 2024, 15, 2144–2153. [Google Scholar] [CrossRef]
  33. Luo, X.J.; Peng, J.; Li, Y.J. Recent advances in the study on capsaicinoids and capsinoids. Eur. J. Pharmacol. 2011, 650, 1–7. [Google Scholar] [CrossRef] [PubMed]
  34. Massaad, C.A.; Klann, E. Reactive oxygen species in the regulation of synaptic plasticity and memory. Antioxid. Redox Signal. 2011, 14, 2013–2054. [Google Scholar] [CrossRef]
  35. Fu, Y.; Koo, M.W.L. EGCG protects HT-22 cells against glutamate-induced oxidative stress. Neurotox. Res. 2006, 10, 23–29. [Google Scholar] [CrossRef]
  36. Jin, M.H.; Chen, D.Q.; Jin, Y.H.; Han, Y.H.; Sun, H.N.; Kwon, T. Hispidin inhibits LPS-induced nitric oxide production in BV-2 microglial cells via ROS-dependent MAPK signaling. Exp. Ther. Med. 2021, 22, 1–9. [Google Scholar] [CrossRef] [PubMed]
  37. Shin, H.-C.; Cho, J.-Y.; Lee, K.H.; Ma, Y.-K.; Jeong, J.H.; Lee, H.J.; Park, K.-H.; Moon, J.-H. Diterpene glycosides from Korean fermented red pepper paste (gochujang) and their origin. Food Chem. 2012, 130, 1024–1030. [Google Scholar] [CrossRef]
  38. Ma, Q.-G.; Xu, K.; Sang, Z.-P.; Wei, R.-R.; Liu, W.-M.; Su, Y.-L.; Yang, J.-B.; Wang, A.-G.; Ji, T.-F.; Li, L.-J. Alkenes with antioxidative activities from Murraya koenigii (L.) Spreng. Bioorg Med. Chem. Lett. 2016, 26, 799–803. [Google Scholar] [CrossRef]
  39. Liu, Y.; Nair, M.G. Non-pungent functional food components in the water extracts of hot peppers. Food Chem. 2010, 122, 731–736. [Google Scholar] [CrossRef]
  40. Chauhan, G.; Roy, K.; Kumar, G.; Kumari, P.; Alam, S.; Kishore, K.; Panjwani, U.; Ray, K. Distinct influence of COX-1 and COX-2 on neuroinflammatory response and associated cognitive deficits during high altitude hypoxia. Neuropharmacology 2019, 146, 138–148. [Google Scholar] [CrossRef]
  41. Lee, H.-Y.; Ro, N.-Y.; Jeong, H.-J.; Kwon, J.-K.; Jo, J.; Ha, Y.; Jung, A.; Han, J.-W.; Venkatesh, J.; Kang, B.-C. Genetic diversity and population structure analysis to construct a core collection from a large Capsicum germplasm. BMC Genet. 2016, 17, 142. [Google Scholar] [CrossRef] [PubMed]
  42. Assefa, S.T.; Yang, E.Y.; Asamenew, G.; Kim, H.W.; Cho, M.C.; Lee, J. Identification of α-Glucosidase Inhibitors from Leaf Extract of Pepper (Capsicum spp.) through Metabolomic Analysis. Metabolites 2021, 11, 649–668. [Google Scholar] [CrossRef] [PubMed]
Plants 13 02820 g001aPlants 13 02820 g001b
Figure 1. Protective effects of the 40 genetic resources from Capsicum annuum extracts on glutamate-induced HT22 cells. HT22 cells were pre-treated with 23OM01–40 (50–200 μg/mL) for 3 h and then stimulated with glutamate (5 mM) for 24 h. Cell viability was then detected. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05; *** p < 0.001 compared with the glutamate group. N-acetyl-cysteine (NAC, 1 mM) was used as a positive control.
Figure 1. Protective effects of the 40 genetic resources from Capsicum annuum extracts on glutamate-induced HT22 cells. HT22 cells were pre-treated with 23OM01–40 (50–200 μg/mL) for 3 h and then stimulated with glutamate (5 mM) for 24 h. Cell viability was then detected. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05; *** p < 0.001 compared with the glutamate group. N-acetyl-cysteine (NAC, 1 mM) was used as a positive control.
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Figure 2. Protective effect of 23OM18 on glutamate-induced HT22 cells (A), and ROS production (B,C). Cells were pre-treated with 23OM18 at concentrations of 50–200 μg/mL for 3 h, followed by stimulation with glutamate (5 mM) for 24 h. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05; *** p < 0.001 compared with the glutamate-treated group.
Figure 2. Protective effect of 23OM18 on glutamate-induced HT22 cells (A), and ROS production (B,C). Cells were pre-treated with 23OM18 at concentrations of 50–200 μg/mL for 3 h, followed by stimulation with glutamate (5 mM) for 24 h. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05; *** p < 0.001 compared with the glutamate-treated group.
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Figure 3. Effects of 23OM18 on the MAPK-JNK signaling pathway in glutamate-induced HT22 cells (A,B). Cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with glutamate (5 mM) for 8 h. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05 compared with the glutamate-treated group.
Figure 3. Effects of 23OM18 on the MAPK-JNK signaling pathway in glutamate-induced HT22 cells (A,B). Cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with glutamate (5 mM) for 8 h. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05 compared with the glutamate-treated group.
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Figure 4. Inhibitory effects of 23OM18 on LPS-induced cytokine secretion in BV2 cells: nitrite (A), TNF-α (B), IL-6 (C), and PGE2 (D). Cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with LPS (0.5 μg/mL) for 24 h. Data are presented as the mean ± standard deviation (n = 3). ** p < 0.01 *** p < 0.001 compared with the LPS-treated group. Dexamethasone (DEXA) was used as a positive control.
Figure 4. Inhibitory effects of 23OM18 on LPS-induced cytokine secretion in BV2 cells: nitrite (A), TNF-α (B), IL-6 (C), and PGE2 (D). Cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with LPS (0.5 μg/mL) for 24 h. Data are presented as the mean ± standard deviation (n = 3). ** p < 0.01 *** p < 0.001 compared with the LPS-treated group. Dexamethasone (DEXA) was used as a positive control.
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Plants 13 02820 g005
Figure 5. Effects of 23OM18 on LPS-induced iNOS and COX-2 expression on BV2 cells (A,B). Cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with LPS (0.5 μg/mL) for 24 h. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05 compared with the LPS-treated group.
Figure 5. Effects of 23OM18 on LPS-induced iNOS and COX-2 expression on BV2 cells (A,B). Cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with LPS (0.5 μg/mL) for 24 h. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05 compared with the LPS-treated group.
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Figure 6. Effects of 23OM18 on the NF-κB signaling pathway on LPS-induced BV2 cells (A–C). Cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with LPS (0.5 μg/mL) for 15 min. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05 compared with the LPS-treated group.
Figure 6. Effects of 23OM18 on the NF-κB signaling pathway on LPS-induced BV2 cells (A–C). Cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with LPS (0.5 μg/mL) for 15 min. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05 compared with the LPS-treated group.
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Figure 7. Effects of 23OM18 on the MAPK signaling pathway in LPS-induced BV2 cells (A,B). Cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with LPS for 30 min. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05 compared with the glutamate-treated group.
Figure 7. Effects of 23OM18 on the MAPK signaling pathway in LPS-induced BV2 cells (A,B). Cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with LPS for 30 min. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05 compared with the glutamate-treated group.
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Figure 8. Protective effects of 23OM18 on LPS-induced BV2 cells co-cultured with HT22 cells (A–C). In the BV2-HT22 co-culture system, BV2 cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with LPS for 24 h. The viability of HT22 cells was assessed. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05; ** p < 0.01; *** p < 0.001, compared with the LPS-treated group.
Figure 8. Protective effects of 23OM18 on LPS-induced BV2 cells co-cultured with HT22 cells (A–C). In the BV2-HT22 co-culture system, BV2 cells were pre-treated with 23OM18 at concentrations of 100–200 μg/mL for 3 h, followed by stimulation with LPS for 24 h. The viability of HT22 cells was assessed. Data are presented as the mean ± standard deviation (n = 3). * p < 0.05; ** p < 0.01; *** p < 0.001, compared with the LPS-treated group.
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Table 1. Passport data of the 40 genetic resources from Capsicum spp.
Table 1. Passport data of the 40 genetic resources from Capsicum spp.
ClassificationAccessionNameSpeciesOriginIT Number
Breeding material23OM0120AGI022Capsicum annuumNIHHS
23OM0220AGI024Capsicum annuumNIHHS
23OM0320AGI029Capsicum annuumNIHHS
23OM04Peru-5438Capsicum chinenseNIAS284050
23OM05C04776Capsicum frutescensNIAS264142
23OM0620AGI039Capsicum annuumNIHHS
23OM07Geumneung JaeraeCapsicum annuumNIAS32454
23OM08TtungttungchoCapsicum annuumNIAS236435
23OM09Sarospataki tf.Capsicum annuumNIAS237569
23OM10Procede-9927Capsicum frutescensNIAS289309
23OM1120AGI018Capsicum annuumNIHHS
23OM1220AGI001Capsicum annuumNIHHS
23OM1320AGI020Capsicum annuumNIHHS
23OM1420AGI021Capsicum annuumNIHHS
23OM15Daejeon JaeraeCapsicum annuumNIAS229662
23OM16BuyeosamseongCapsicum annuumNIAS286355
23OM17SeonghwansinbangCapsicum annuumNIAS286378
23OM18UiryeonggabeulCapsicum annuumNIAS286389
23OM19GochangjusanCapsicum annuumNIAS286392
23OM2020AGI049Capsicum annuumNIHHS
23OM21TaeanCapsicum annuumNIHHS
23OM22YCM334Capsicum annuumNIHHS
23OM23TF68Capsicum annuumNIHHS
23OM24HabaneroCapsicum chinenseNIHHS
23OM2535009Capsicum annuumNIHHS
23OM2635001Capsicum annuumNIHHS
23OM27SR213Capsicum annuumNIHHS
23OM28SR214Capsicum annuumNIHHS
23OM29HanuriCapsicum annuumNIHHS
23OM30ToktokCapsicum annuumNIHHS
23OM31Start07Capsicum annuumNIHHS
23OM32AVDan1hoCapsicum annuumNIHHS
23OM33JolokiaCapsicum chinenseNIHHS
Commercial cultivar23OM34KallatanCapsicum annuumSakata Korea
23OM35GilsangCapsicum annuumSakata Korea
23OM36NokgwangCapsicum annuumPamhannong
23OM37CheongyangCapsicum annuumPamhannong
23OM38Dangjo MildCapsicum annuumJeil Seed
23OM39Miin PutgochuCapsicum annuumAsia Seed
23OM40Wongi1hoCapsicum annuumNIHHS
Table 2. Major morphological characteristics of the 40 genetic resources from Capsicum spp.
Table 2. Major morphological characteristics of the 40 genetic resources from Capsicum spp.
Plant Height (cm)1st Node Length (cm)Stem Diameter (mm)Leaf Length (cm)Leaf Width (cm)
23OM0183.6 ± 18.034.2 ± 5.012.7 ± 2.314.5 ± 3.35.3 ± 1.2
23OM0275.6 ± 25.835.1 ± 1.111.2 ± 3.813.8 ± 3.85.3 ± 1.5
23OM0371.4 ± 4.331.7 ± 1.412.5 ± 0.615.8 ± 1.26.3 ± 0.7
23OM0446.7 ± 5.414.4 ± 3.011.3 ± 1.79.5 ± 0.94.8 ± 0.6
23OM0573.1 ± 6.736.5 ± 2.811.3 ± 1.417.6 ± 1.510.3 ± 1.0
23OM0664.2 ± 18.518.7 ± 2.511.6 ± 3.39.1 ± 1.63.8 ± 0.6
23OM0779.6 ± 26.425.0 ± 4.88.5 ± 2.38.3 ± 2.13.6 ± 0.9
23OM0871.3 ± 10.016.4 ± 4.19.7 ± 1.56.7 ± 1.03.0 ± 0.4
23OM0961.8 ± 14.227.0 ± 2.013.4 ± 3.215.1 ± 4.26.5 ± 1.8
23OM1056.9 ± 4.533.0 ± 1.810.7 ± 1.116.3 ± 1.58.5 ± 1.2
23OM1179.0 ± 11.127.1 ± 1.412.8 ± 1.19.9 ± 1.04.1 ± 0.4
23OM1272.8 ± 8.128.8 ± 2.811.9 ± 0.811.2 ± 0.74.8 ± 0.4
23OM1386.8 ± 4.833.2 ± 2.912.8 ± 0.815.4 ± 0.66.0 ± 0.5
23OM1489.9 ± 7.035.0 ± 1.112.6 ± 0.715.9 ± 1.56.0 ± 0.5
23OM1597.9 ± 9.030.5 ± 2.412.2 ± 1.014.7 ± 0.86.7 ± 0.6
23OM1690.8 ± 12.529.5 ± 4.59.5 ± 0.58.6 ± 1.23.7 ± 0.6
23OM1794.1 ± 7.226.4 ± 4.411.2 ± 0.98.8 ± 1.33.8 ± 0.5
23OM1890.9 ± 6.532.3 ± 2.311.5 ± 0.711.1 ± 1.44.6 ± 0.8
23OM1991.9 ± 10.626.8 ± 2.410.6 ± 1.08.5 ± 0.44.0 ± 0.2
23OM2039.3 ± 5.316.8 ± 2.611.3 ± 0.814.5 ± 1.16.0 ± 0.4
23OM2185.3 ± 18.925.6 ± 3.111.0 ± 2.410.1 ± 1.84.6 ± 0.9
23OM2272.8 ± 7.227.5 ± 2.310.7 ± 1.012.9 ± 1.35.6 ± 0.6
23OM2376.7 ± 20.026.5 ± 3.810.3 ± 2.013.7 ± 2.95.3 ± 1.2
23OM2447.6 ± 3.422.9 ± 2.510.7 ± 0.812.3 ± 0.97.2 ± 0.5
23OM2580.8 ± 6.723.4 ± 1.814.6 ± 1.39.0 ± 1.44.4 ± 1.0
23OM2638.3 ± 11.422.9 ± 4.67.9 ± 1.29.6 ± 0.94.6 ± 0.4
23OM2770.3 ± 4.124.5 ± 2.511.7 ± 1.013.6 ± 1.65.0 ± 0.4
23OM2876.1 ± 7.231.2 ± 2.311.5 ± 0.513.6 ± 0.85.2 ± 0.5
23OM2940.5 ± 2.914.0±1.26.3 ± 0.64.8 ± 0.32.1 ± 0.4
23OM3042.6 ± 13.312.5 ± 2.510.3 ± 1.08.9 ± 1.15.5 ± 0.6
23OM3167.5±12.322.5 ± 2.812.9 ± 1.513.6 ± 2.06.2 ± 0.8
23OM3251.0 ± 11.624.8 ± 1.813.3 ± 2.914.6 ± 4.16.5 ± 1.5
23OM3364.3 ± 8.928.0 ± 6.811.9 ± 0.815.3 ± 2.39.0 ± 1.4
23OM3491.5 ± 8.026.4 ± 2.412.8 ± 1.810.2 ± 1.94.5 ± 0.8
23OM3571.1 ± 4.421.9 ± 2.112.4 ± 0.910.2 ± 1.24.5 ± 0.6
23OM3691.3 ± 9.627.2 ± 2.112.8 ± 1.312.0 ± 1.85.3 ± 0.9
23OM37111.6 ± 4.029.7 ± 2.414.7 ± 1.19.7 ± 1.14.2 ± 0.5
23OM3871.0 ± 6.730.8 ± 0.713.7 ± 0.914.9 ± 2.26.6 ± 1.1
23OM3976.0 ± 4.022.6 ± 1.813.2 ± 0.810.4 ± 1.04.1 ± 0.7
23OM4077.3 ± 6.228.6 ± 4.012.3 ± 1.211.8 ± 0.85.7 ± 0.4
Table 3. Cell protection EC50 of 23OM16-23OM20 on glutamate-induced HT22 cells.
Table 3. Cell protection EC50 of 23OM16-23OM20 on glutamate-induced HT22 cells.
AccessionNameCell Protection EC50 (μg/mL)
23OM16Buyeosamseong167.5 ± 0.8095
23OM17Seonghwansinbang166.4 ± 0.8032
23OM18Uiryeonggabeul102.6 ± 0.2934
23OM19Gochangjusan147.4 ± 1.109
23OM2020AGI049167.2 ± 8.047
Table 4. Relative percentages of secondary metabolite in four genetic resources from Capsicum spp. (%).
Table 4. Relative percentages of secondary metabolite in four genetic resources from Capsicum spp. (%).
No.Expected
RT (min)		Component NameFormulaObserved
m/z		Observed
RT (min)		AdductsAverage of Relative Percentage (%)
OM-16OM-17OM-18OM-19OM-20
10.59Quinic acidC7H12O6191.010.63−H8.0176.4106.8849.50710.328
20.79Citric acidC6H8O7191.050.8−H4.5075.1323.8114.7973.265
30.92N-caffeoylputrescineC13H18N2O3249.120.91−H, +HCOO7.3212.3914.2874.2994.965
41.53Chlorogenic acidC16H18O9353.091.5-H2.2864.0521.8224.1361.573
52.48MaltoseC12H22O11341.092.39−H, +HCOO0.006N.DN.DN.DN.D
62.81Luteolin-7-O-apiofuranosyl(1→2)
glucopyranoside		C26H28O15579.132.82−H, +HCOO27.14925.18626.80026.06424.708
72.91Luteolin-7-O-glucopyranosideC21H20O11447.092.91−H, +HCOO12.0576.82611.89511.31910.833
83.31Apigenin-7-apiosylglucosideC26H28O14563.143.3−H, +HCOO2.18819.4122.1901.1675.491
93.39Luteolin7-(2-O-apiosyl-6-O-malonyl) glucosideC29H30O18665.143.39−H18.30812.83516.88721.86117.799
103.52Luteolin 7-0-β-d-(6″-acetyl)-glucopyranosideC23H22O12489.13.51−H3.5161.1842.7694.6584.085
113.9MalonylapiinC29H30O17649.143.89−H0.4663.3460.3740.4861.73
125.13Capsianoside IIIC50H84O261145.525.14−H, +HCOO0.5470.8090.7350.3670.950
135.67Capsianoside IC32H52O14659.335.68−H0.4840.7200.6660.5921.616
145.94Capsianoside IIC50H84O251129.535.95−H, +HCOO7.4147.44711.6324.5597.090
156.37Capsianoside new IIIC53H86O281169.536.36−H5.5673.9559.0576.1095.107
1610.86Capsianoside VIIIC50H84O251129.5310.85−H, +HCOO0.1690.2970.1920.0790.487
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MDPI and ACS Style

Dong, L.; Choi, B.-R.; Jeong, H.B.; Lee, H.; Liu, Z.; Yoon, D.; Lee, H.E.; Lee, D.-S.; Lee, D.Y. Effects of Leaf Extracts from Genetic Resource of Capsicum spp. on Neuroprotection and Anti-Neuroinflammation in HT22 and in BV2 Cells. Plants 2024, 13, 2820. https://doi.org/10.3390/plants13192820

AMA Style

Dong L, Choi B-R, Jeong HB, Lee H, Liu Z, Yoon D, Lee HE, Lee D-S, Lee DY. Effects of Leaf Extracts from Genetic Resource of Capsicum spp. on Neuroprotection and Anti-Neuroinflammation in HT22 and in BV2 Cells. Plants. 2024; 13(19):2820. https://doi.org/10.3390/plants13192820

Chicago/Turabian Style

Dong, Linsha, Bo-Ram Choi, Hyo Bong Jeong, Hwan Lee, Zhiming Liu, Dahye Yoon, Hye Eun Lee, Dong-Sung Lee, and Dae Young Lee. 2024. "Effects of Leaf Extracts from Genetic Resource of Capsicum spp. on Neuroprotection and Anti-Neuroinflammation in HT22 and in BV2 Cells" Plants 13, no. 19: 2820. https://doi.org/10.3390/plants13192820

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