Induction of mitochondrial-dependent apoptosis, activation of mitochondrial ATPase and cytochrome c release by the methanol extract of Funtumia elastica stem bark
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Fatima B. Musa
,
Tolulope A. Oyedeji
,
Adeola O. Olowofolahan
,
Hammed O. Faleke
Abstract
Objectives
Natural compounds that can induce the opening of the mitochondrial membrane permeability transition (MMPT) pore may be useful therapeutic agents in treating diseases associated with mitochondrial dysfunction e.g. cancer, diabetes, and neurodegenerative diseases. This pore represents a promising target for therapeutic intervention. Therefore, this study investigated the potential of the methanol extract of Funtumia elastica stem bark on the MMPT pore, mitochondrial ATPase (mATPase), cytochrome c release (cyt c), and mitochondrial lipid peroxidation (mLPO) in rat liver.
Methods
Male Wistar rats (100–120 g) were used in this study. Differential centrifugation was used to isolate mitochondria from rat liver. MMPT pore opening, mATPase activity, cyt c, and mLPO were assayed.
Results
The results indicate that the methanol extract of F. elastica induced MMPT pore opening in the absence of calcium ions. Also, in the presence of calcium ions, the extract significantly (p<0.05) reversed the opening of the MMPT pore by 21.0, 30.0, 34.0, and 38.0 % at 12, 36, 60, and 84 μg/mL, respectively. The extract activated mitochondrial ATPase activity significantly (p<0.05) compared to the control. The extract elevated cytochrome c release with increasing extract concentration relative to the control. The extract also inhibited iron-induced mitochondrial lipid peroxidation by 29.0, 38.7, 59.9, 83.0, and 87.0 % at 150, 300, 600, 1,200, and 2,400 μg/mL, respectively.
Conclusions
Our results showed that the methanol extract of F. elastica contains potent phytochemicals that can trigger MMPT pore opening, activate mATPase, cyt c, and inhibit mLPO. This extract may find use in diseases associated with apoptosis dysfunction.
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Research ethics: Certificate number: UI–ACUREC⁄038-0521/11.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interests: The authors state no conflict of interest.
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Research funding: None declared.
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Data availability: Data available on request.
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