TLC-bioautography-guided identification and assessment of the antibacterial compounds from Feijoa sellowiana.

IF 3 3区生物学 Q2 BIOCHEMICAL RESEARCH METHODS

Phytochemical Analysis Pub Date : 2024-09-05 DOI:10.1002/pca.3448

Wenliang Xu, Danxia Shi, Kuanmin Chen, David G Popovich

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引用次数: 0

Abstract

Introduction: A rapid procedure was developed for the targeted isolation and assessment of antibacterial compounds from plant-based materials. The effectiveness of this method was demonstrated using Feijoa sellowiana fruit peels.

Objective: The objectives of this study are as follows: develop an efficient procedure utilizing direct thin-layer chromatography (TLC)-bioautography to facilitate the targeting, identification, and purification of antibacterial compounds from plant extracts and delineate a method based on TLC-bioautography to determine the minimum effective dose (MED), alongside a colorimetric broth microdilution aided by high-performance liquid chromatography (HPLC) for evaluating the isolated active compounds.

Methodology: Active compounds were targeted using TLC-bioautography against Staphylococcus aureus, and the identification was achieved through liquid chromatography-mass spectrometry (LC-MS) combined with Compound Discoverer. Purification was carried out using a customized separation method. The structure was confirmed using nuclear magnetic resonance (NMR) spectroscopy. The MED, minimum inhibitory concentration (MIC), and minimum bactericidal concentration (MBC) were determined by two enhanced antibacterial assays.

Results: The main antibacterial compound identified was flavone. A TLC-bioautography-based antibacterial assay and a colorimetric broth microdilution assisted by HPLC were described as the enhanced antibacterial assay protocols. The MED, MIC, and MBC of flavone against S. aureus were found to be 4.2-5.2 μg/cm², 225-275 μg/mL, and 550-650 μg/mL, respectively. Similarly, the MED, MIC, and MBC against Escherichia coli were determined to be 5.2-6.1 μg/cm², 325-375 μg/mL, and 375-425 μg/mL, respectively.

Conclusion: This study proposed an enhanced bioassay-guided separation technique for the isolation of antibacterial compounds from plants, along with two improved methods for assessing the antibacterial efficacy of insoluble or colored compounds.

查看原文本刊更多论文

利用 TLC 生物自动层析技术鉴定和评估黄花飞燕草中的抗菌化合物。

介绍：开发了一种从植物材料中定向分离和评估抗菌化合物的快速程序。该方法的有效性已在飞黄果果皮中得到验证：本研究的目标如下：利用直接薄层色谱（TLC）-生物自动层析技术开发一种高效的程序，以促进从植物提取物中定向分离、鉴定和纯化抗菌化合物；确定一种基于 TLC-生物自动层析技术的方法，以确定最小有效剂量（MED），同时利用高效液相色谱（HPLC）辅助比色肉汤微稀释法评估分离出的活性化合物：采用 TLC 生物自动层析法对金黄色葡萄球菌进行活性化合物靶标定位，并结合 Compound Discoverer 通过液相色谱-质谱联用仪（LC-MS）进行鉴定。采用定制的分离方法进行了纯化。利用核磁共振（NMR）光谱确认了其结构。通过两种增强抗菌试验确定了 MED、最低抑菌浓度 (MIC) 和最低杀菌浓度 (MBC)：结果：鉴定出的主要抗菌化合物是黄酮。基于 TLC-生物自动层析的抗菌测定法和 HPLC 辅助的比色肉汤微稀释法被描述为增强型抗菌测定法。结果发现，黄酮对金黄色葡萄球菌的 MED、MIC 和 MBC 分别为 4.2-5.2 μg/cm2、225-275 μg/mL、550-650 μg/mL。同样，对大肠杆菌的 MED、MIC 和 MBC 分别为 5.2-6.1 μg/cm2、325-375 μg/mL 和 375-425 μg/mL：本研究提出了一种用于从植物中分离抗菌化合物的增强型生物测定指导分离技术，以及两种用于评估不溶性或有色化合物抗菌功效的改进方法。

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.