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真菌病原体的基因组规模代谢模型:过去、现在和未来。

Genome-Scale Metabolic Models in Fungal Pathogens: Past, Present, and Future.

机构信息

Grupo de Investigación Celular y Molecular de Microorganismos Patógenos (CeMoP), Department of Biological Science, Faculty of Science, Universidad de los Andes, Bogotá 111711, Colombia.

Grupo de Diseño de Productos y Procesos (GDPP), Departament of Chemical and Food Engineering, Faculty of Engineering, Universidad de los Andes, Bogotá 111711, Colombia.

出版信息

Int J Mol Sci. 2024 Oct 9;25(19):10852. doi: 10.3390/ijms251910852.

Abstract

Fungi are diverse organisms with various characteristics and functions. Some play a role in recycling essential elements, such as nitrogen and carbon, while others are utilized in the food and drink production industry. Some others are known to cause diseases in various organisms, including humans. Fungal pathogens cause superficial, subcutaneous, and systemic infections. Consequently, many scientists have focused on studying the factors contributing to the development of human diseases. Therefore, multiple approaches have been assessed to examine the biology of these intriguing organisms. The genome-scale metabolic models (GEMs) have demonstrated many advantages to microbial metabolism studies and the ability to propose novel therapeutic alternatives. Despite significant advancements, much remains to be elucidated regarding the use of this tool for investigating fungal metabolism. This review aims to compile the data provided by the published GEMs of human fungal pathogens. It gives specific examples of the most significant contributions made by these models, examines the advantages and difficulties associated with using such models, and explores the novel approaches suggested to enhance and refine their development.

摘要

真菌是具有各种特征和功能的多样化生物体。有些在循环利用氮和碳等基本元素方面发挥作用,而另一些则用于食品和饮料生产行业。还有一些已知会导致各种生物体(包括人类)患病。真菌病原体引起浅表、皮下和全身感染。因此,许多科学家专注于研究导致人类疾病的发展因素。因此,已经评估了多种方法来研究这些有趣生物体的生物学特性。基于基因组规模的代谢模型(GEMs)已经展示了在微生物代谢研究中的许多优势,并且能够提出新的治疗替代方案。尽管取得了重大进展,但在利用该工具研究真菌代谢方面仍有许多需要阐明的地方。本综述旨在汇集已发表的人类真菌病原体 GEM 的数据。它提供了这些模型的最重要贡献的具体示例,检查了使用此类模型的优点和困难,并探讨了建议的新方法来增强和完善它们的发展。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2237/11476900/73d57a09c2cc/ijms-25-10852-g001.jpg

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