Guhe Vrushali, Ingale Prajakta, Tambekar Anil, Singh Shailza
National Centre for Cell Science, NCCS Complex, Ganeshkhind, SPPU Campus, Pune, India.
Front Mol Biosci. 2023 Apr 21;10:1113249. doi: 10.3389/fmolb.2023.1113249. eCollection 2023.
Autophagy is a contentious issue in leishmaniasis and is emerging as a promising therapeutic regimen. Published research on the impact of autophagic regulation on survival is inconclusive, despite numerous pieces of evidence that spp. triggers autophagy in a variety of cell types. The mechanistic approach is poorly understood in the parasite as autophagy is significant in both and the host. Herein, this review discusses the autophagy proteins that are being investigated as potential therapeutic targets, the connection between autophagy and lipid metabolism, and microRNAs that regulate autophagy and lipid metabolism. It also highlights the use of systems biology to develop novel autophagy-dependent therapeutics for leishmaniasis by utilizing artificial intelligence (AI), machine learning (ML), mathematical modeling, network analysis, and other computational methods. Additionally, we have shown many databases for autophagy and metabolism in parasites that suggest potential therapeutic targets for intricate signaling in the autophagy system. In a nutshell, the detailed understanding of the dynamics of autophagy in conjunction with lipids and miRNAs unfolds larger dimensions for future research.
自噬在利什曼病中是一个有争议的问题,并且正成为一种有前景的治疗方案。尽管有大量证据表明利什曼原虫在多种细胞类型中触发自噬,但关于自噬调节对其生存影响的已发表研究尚无定论。在这种寄生虫中,由于自噬在寄生虫和宿主中都很重要,其机制方法仍知之甚少。在此,本综述讨论了正在作为潜在治疗靶点进行研究的自噬蛋白、自噬与脂质代谢之间的联系,以及调节自噬和脂质代谢的微小RNA。它还强调了利用系统生物学,通过人工智能(AI)、机器学习(ML)、数学建模、网络分析和其他计算方法,开发针对利什曼病的新型自噬依赖性疗法。此外,我们展示了许多关于利什曼原虫自噬和代谢的数据库,这些数据库揭示了自噬系统中复杂信号传导的潜在治疗靶点。简而言之,对自噬与脂质和微小RNA动态关系的详细理解为未来研究展现了更广阔的维度。