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利用拉曼光谱早期检测拟南芥和芸苔的真菌感染

Early detection of fungal infection of Arabidopsis and brassica by Raman spectroscopy.

作者信息

Kuo Song-Yi, Chiu Ling-Ying, Jain Ekta, Singh Gajendra Pratap, Bin Jamaludin Muhammad Nabil Syafiq, Ram Rajeev J, Chua Nam-Hai

机构信息

Temasek Life Sciences Laboratory, 1 Research Link, National University of Singapore, Singapore, Singapore.

Disruptive and Sustainable Technologies for Agricultural Precision, Singapore-MIT Alliance for Research and Technology, Singapore, Singapore.

出版信息

Front Plant Sci. 2025 Aug 15;16:1649206. doi: 10.3389/fpls.2025.1649206. eCollection 2025.

DOI:10.3389/fpls.2025.1649206
PMID:40894503
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12394222/
Abstract

Here, we used Raman spectroscopy to characterize the effects of chitin treatment and fungal inoculations on and Brassica vegetables. Chitin, a recognized fungal pathogen-associated molecular pattern (PAMP), elicited a dose dependent positive Elicitor Response Index (ERI) in wild-type Arabidopsis. Mutant plants lacking chitin receptors ( and ) displayed minimal ERI, whereas mutant deficient in the bacterial-specific flg22 receptor was hyper-responsive. These results confirm critical role of chitin receptors in activating downstream pathways and highlighting distinct responses in two separate pattern-triggered immunity (PTI) systems. Inoculations of and induced significant changes in Infection Response Index (IRI) values, with the former giving positive IRI at 12-48 hours post-inoculation whereas the latter exhibited a transient negative IRI before transitioning to positive values. Notably, Raman shifts could predict fungal infection before the appearance of visible symptoms, establishing Raman shifts as a potential early diagnostic marker. Comparative analyses of infected Brassica vegetables revealed varied sensitivity to fungal pathogens and a correlation between symptom severity and IRI values. Furthermore, randomized controlled trials validated the reliability of Raman technology for early, pre-symptomatic detection of fungal infections, achieving an accuracy rate of 76.2% in Arabidopsis and 72.5% in Pak-Choy (). Principal component analysis differentiated Raman spectral features associated with fungal and bacterial infections, emphasizing their unique profiles and reinforcing the utility of Raman spectroscopy for early detection of pathogen-related plant stress. Our work supports the application of non-invasive diagnostic techniques in agricultural practices, enabling timely intervention against crop diseases.

摘要

在此,我们使用拉曼光谱法来表征几丁质处理和真菌接种对拟南芥和芸苔属蔬菜的影响。几丁质是一种公认的真菌病原体相关分子模式(PAMP),在野生型拟南芥中引发了剂量依赖性的正向激发子反应指数(ERI)。缺乏几丁质受体(和)的突变植株表现出最小的ERI,而缺乏细菌特异性flg22受体的突变体则反应过度。这些结果证实了几丁质受体在激活下游途径中的关键作用,并突出了两个独立的模式触发免疫(PTI)系统中的不同反应。接种和诱导了感染反应指数(IRI)值的显著变化,前者在接种后12 - 48小时呈现正向IRI,而后者在转变为正值之前表现出短暂的负向IRI。值得注意的是,拉曼位移可以在可见症状出现之前预测真菌感染,确立了拉曼位移作为一种潜在的早期诊断标志物。对受感染的芸苔属蔬菜的比较分析揭示了对真菌病原体的不同敏感性以及症状严重程度与IRI值之间的相关性。此外,随机对照试验验证了拉曼技术用于真菌感染早期症状前检测的可靠性,在拟南芥中的准确率为76.2%,在小白菜()中的准确率为72.5%。主成分分析区分了与真菌和细菌感染相关的拉曼光谱特征,强调了它们的独特谱图,并加强了拉曼光谱用于早期检测病原体相关植物胁迫的效用。我们的工作支持在农业实践中应用非侵入性诊断技术,以便及时干预作物疾病。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/cda6d6404346/fpls-16-1649206-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/6e618a3dbca5/fpls-16-1649206-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/2d2ed7b9f3b2/fpls-16-1649206-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/de6101f1572d/fpls-16-1649206-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/69eddc103cd3/fpls-16-1649206-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/cda6d6404346/fpls-16-1649206-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/6e618a3dbca5/fpls-16-1649206-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/2d2ed7b9f3b2/fpls-16-1649206-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/de6101f1572d/fpls-16-1649206-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/69eddc103cd3/fpls-16-1649206-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/51c8/12394222/cda6d6404346/fpls-16-1649206-g005.jpg

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Elife. 2024 Jul 19;12:RP92110. doi: 10.7554/eLife.92110.
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