Harnessing Molecular and Bioactivity Network Analysis to Prioritize Antibacterial Compound Isolation From Ant-Associated Fungi.

IF 3 3区生物学 Q2 BIOCHEMICAL RESEARCH METHODS

Phytochemical Analysis Pub Date : 2025-07-01 Epub Date: 2025-01-30 DOI:10.1002/pca.3513

Ángel S Aguilar-Colorado, Jesús Morales-Jiménez, José Rivera-Chávez

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引用次数: 0

Abstract

Introduction: Antimicrobial resistance is a global public health problem that requires the development of new bioactive compounds. In this context, metabolomic analyses can expedite the research of fungal metabolites as a valuable resource.

Objectives: To investigate the metabolic profiles and isolate antibacterial compounds from micromycetes associated with Mexican cloud forest ants by utilizing network analysis of their chemical and bioactivity data.

Material and methods: 248 fungal strains isolated from six ant's species, soil of their anthills, and soil of the surroundings were evaluated for their in vitro inhibition growth of extensively drug-resistant Acinetobacter baumannii and hypervirulent Klebsiella pneumoniae; subsequently, their metabolites were dereplicated and analyzed by molecular networking and compound activity mapping from spectrometric data. Prioritization of some fungi for isolation of their major constituents was performed, and their structures were established by spectroscopic and spectrometric analysis and their bioactivity determined.

Results: From the fungal collection, 15 secondary metabolites (1-15) were dereplicated, and 10 compounds (16-25), including the new (E)-tridec-7-ene-3,5,6,10-tetraol (25), were isolated from Ascomycetes of Trichoderma, Cladosporium, and Clonostachys genera. Compounds 16-18 stood out for being bioactive. This study is the first report of antibacterial activity against A. baumannii for the tricyclic pyridin-2-ones deoxy-PF1140 (16) and PF1140 (17), with minimum inhibitory concentration of 50 μg/mL.

Conclusion: Network analysis and dereplication proved effective in bioprospecting for antibacterial compounds, offering valuable insights into the chemical diversity of cloud forest soil fungi and their potential applications. Moreover, this study broadens the knowledge of fungal secondary metabolites linked to leafcutter, fire, and warrior ants.

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利用分子和生物活性网络分析优先从抗相关真菌中分离抗菌化合物。

抗菌素耐药性是一个全球性的公共卫生问题，需要开发新的生物活性化合物。在这种情况下，代谢组学分析可以加快真菌代谢物的研究，作为一种宝贵的资源。目的：利用化学和生物活性数据的网络分析，研究墨西哥云林蚁相关微菌的代谢特征并分离抗菌化合物。材料和方法：从6种蚂蚁、蚁丘土壤和周围土壤中分离248株真菌，对其体外抑制广泛耐药鲍曼不动杆菌和高毒力肺炎克雷伯菌的生长进行了评价；随后，通过分子网络和光谱数据的化合物活性定位分析了它们的代谢物。对部分真菌的主要成分进行了优选，通过光谱和光谱分析确定了其结构，并测定了其生物活性。结果：从真菌收集物中分离得到木霉、枝孢菌和Clonostachys属子囊菌的15个次级代谢产物（1 ~ 15），10个化合物（16 ~ 25），包括新的(E)-三烯-7-烯-3,5,6,10-四醇（25）。化合物16-18具有生物活性。本研究首次报道了三环吡啶-2-酮脱氧-PF1140（16）和PF1140（17）对鲍曼不稳定菌的抑菌活性，最低抑菌浓度为50 μg/mL。结论：网络分析和去复制在抗菌化合物的生物勘探中是有效的，为了解云雾林土壤真菌的化学多样性及其潜在的应用前景提供了有价值的见解。此外，该研究拓宽了与切叶蚁、火蚁和战蚁相关的真菌次生代谢物的知识。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Phytochemical Analysis 生物-分析化学

CiteScore

6.00

自引率

6.10%

发文量

审稿时长

1.7 months

期刊介绍： Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.