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衰减全反射傅里叶变换红外光谱揭示了克隆日本虎杖中特定环境的表型。

Attenuated total reflection Fourier-transform infrared spectroscopy reveals environment specific phenotypes in clonal Japanese knotweed.

机构信息

Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK.

Phlorum Ltd, Brighton, BN2 6AH, UK.

出版信息

BMC Plant Biol. 2024 Aug 13;24(1):769. doi: 10.1186/s12870-024-05200-7.

DOI:10.1186/s12870-024-05200-7
PMID:39135189
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11321083/
Abstract

BACKGROUND

Japanese knotweed (Reynoutria japonica var. japonica), a problematic invasive species, has a wide geographical distribution. We have previously shown the potential for attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy and chemometrics to segregate regional differentiation between Japanese knotweed plants. However, the contribution of environment to spectral differences remains unclear. Herein, the response of Japanese knotweed to varied environmental habitats has been studied. Eight unique growth environments were created by manipulation of the red: far-red light ratio (R: FR), water availability, nitrogen, and micronutrients. Their impacts on plant growth, photosynthetic parameters, and ATR-FTIR spectral profiles, were explored using chemometric techniques, including principal component analysis (PCA), linear discriminant analysis, support vector machines (SVM) and partial least squares regression. Key wavenumbers responsible for spectral differences were identified with PCA loadings, and molecular biomarkers were assigned. Partial least squared regression (PLSR) of spectral absorbance and root water potential (RWP) data was used to create a predictive model for RWP.

RESULTS

Spectra from plants grown in different environments were differentiated using ATR-FTIR spectroscopy coupled with SVM. Biomarkers highlighted through PCA loadings corresponded to several molecules, most commonly cell wall carbohydrates, suggesting that these wavenumbers could be consistent indicators of plant stress across species. R: FR most affected the ATR-FTIR spectra of intact dried leaf material. PLSR prediction of root water potential achieved an R2 of 0.8, supporting the potential use of ATR-FTIR spectrometers as sensors for prediction of plant physiological parameters.

CONCLUSIONS

Japanese knotweed exhibits environmentally induced phenotypes, indicated by measurable differences in their ATR-FTIR spectra. This high environmental plasticity reflected by key biomolecular changes may contribute to its success as an invasive species. Light quality (R: FR) appears critical in defining the growth and spectral response to environment. Cross-species conservation of biomarkers suggest that they could function as indicators of plant-environment interactions including abiotic stress responses and plant health.

摘要

背景

作为一种具有广泛地理分布的有害入侵物种,日本虎杖(Reynoutria japonica var. japonica)具有很强的环境适应能力。我们之前已经证明,衰减全反射傅里叶变换红外(ATR-FTIR)光谱和化学计量学在区分日本虎杖植物的区域分化方面具有潜力。然而,环境对光谱差异的贡献仍不清楚。在此,研究了日本虎杖对不同环境生境的响应。通过操纵红光:远红光比值(R: FR)、水分可用性、氮和微量元素,创建了八个独特的生长环境。使用化学计量技术,包括主成分分析(PCA)、线性判别分析、支持向量机(SVM)和偏最小二乘回归,研究了它们对植物生长、光合参数和 ATR-FTIR 光谱谱图的影响。使用 PCA 载荷确定了导致光谱差异的关键波数,并分配了分子生物标志物。通过偏最小二乘回归(PLSR)对光谱吸光度和根水势(RWP)数据进行建模,以创建 RWP 的预测模型。

结果

使用 ATR-FTIR 光谱结合 SVM 对在不同环境中生长的植物的光谱进行了区分。通过 PCA 载荷突出的生物标志物对应于几种分子,最常见的是细胞壁碳水化合物,这表明这些波数可能是跨物种植物应激的一致指标。R: FR 对完整干燥叶片材料的 ATR-FTIR 光谱影响最大。根水势的 PLSR 预测达到了 0.8 的 R2,支持使用 ATR-FTIR 光谱仪作为预测植物生理参数的传感器。

结论

日本虎杖表现出环境诱导的表型,这可以通过其 ATR-FTIR 光谱的可测量差异来表示。这种由关键生物分子变化反映的高环境可塑性可能有助于其成为入侵物种的成功。光质(R: FR)似乎对定义生长和对环境的光谱响应至关重要。跨物种生物标志物的保守性表明,它们可以作为植物-环境相互作用的指标,包括非生物胁迫反应和植物健康。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/4106bc91ac86/12870_2024_5200_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/fdb63070fa7c/12870_2024_5200_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/bc57576e0f2a/12870_2024_5200_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/902b313f0bb2/12870_2024_5200_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/2d8350422f05/12870_2024_5200_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/4106bc91ac86/12870_2024_5200_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/fdb63070fa7c/12870_2024_5200_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/bc57576e0f2a/12870_2024_5200_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/902b313f0bb2/12870_2024_5200_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/2d8350422f05/12870_2024_5200_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f8e/11321083/4106bc91ac86/12870_2024_5200_Fig5_HTML.jpg

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