Combining Fourier-transform infrared spectroscopy and multivariate analysis for chemotyping of cell wall composition in Mungbean (Vigna radiata (L.) Wizcek).

IF 4.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Shouvik Das, Vikrant Bhati, Bhagwat Prasad Dewangan, Apurva Gangal, Gyan Prakash Mishra, Harsh Kumar Dikshit, Prashant Anupama Mohan Pawar
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引用次数: 0

Abstract

Background: Dissection of complex plant cell wall structures demands a sensitive and quantitative method. FTIR is used regularly as a screening method to identify specific linkages in cell walls. However, quantification and assigning spectral bands to particular cell wall components is still a major challenge, specifically in crop species. In this study, we addressed these challenges using ATR-FTIR spectroscopy as it is a high throughput, cost-effective and non-destructive approach to understand the plant cell wall composition. This method was validated by analysing different varieties of mungbean which is one of the most important legume crops grown widely in Asia.

Results: Using standards and extraction of a specific component of cell wall components, we assigned 1050-1060 cm-1 and 1390-1420 cm-1 wavenumbers that can be widely used to quantify cellulose and lignin, respectively, in Arabidopsis, Populus, rice and mungbean. Also, using KBr as a diluent, we established a method that can relatively quantify the cellulose and lignin composition among different tissue types of the above species. We further used this method to quantify cellulose and lignin in field-grown mungbean genotypes. The ATR-FTIR-based study revealed the cellulose content variation ranges from 27.9% to 52.3%, and the lignin content variation ranges from 13.7% to 31.6% in mungbean genotypes.

Conclusion: Multivariate analysis of FT-IR data revealed differences in total cell wall (600-2000 cm-1), cellulose (1000-1100 cm-1) and lignin (1390-1420 cm-1) among leaf and stem of four plant species. Overall, our data suggested that ATR-FTIR can be used for the relative quantification of lignin and cellulose in different plant species. This method was successfully applied for rapid screening of cell wall composition in mungbean stem, and similarly, it can be used for screening other crops or tree species.

结合傅立叶变换红外光谱和多元分析对绿豆(Vigna radiata (L.) Wizcek)细胞壁成分进行化学分型。
背景:剖析复杂的植物细胞壁结构需要一种灵敏的定量方法。傅立叶变换红外光谱经常被用作筛选方法,以确定细胞壁中的特定连接。然而,量化和将光谱带分配给特定的细胞壁成分仍然是一项重大挑战,特别是在农作物物种中。在本研究中,我们使用 ATR-FTIR 光谱来解决这些难题,因为它是一种了解植物细胞壁成分的高通量、高成本效益和非破坏性的方法。该方法通过分析不同品种的绿豆进行了验证,绿豆是亚洲广泛种植的最重要豆类作物之一:结果:通过使用标准和提取细胞壁成分的特定组分,我们确定了 1050-1060 cm-1 和 1390-1420 cm-1 波长,可分别广泛用于定量分析拟南芥、杨树、水稻和绿豆中的纤维素和木质素。此外,我们还建立了一种以 KBr 为稀释剂的方法,可相对量化上述物种不同组织类型中的纤维素和木质素成分。我们进一步利用该方法对田间种植的绿豆基因型中的纤维素和木质素进行了定量分析。基于 ATR-FTIR 的研究表明,绿豆基因型中纤维素含量的变化范围为 27.9% 至 52.3%,木质素含量的变化范围为 13.7% 至 31.6%:对傅立叶变换红外光谱数据的多变量分析表明,四种植物的叶和茎在细胞壁总量(600-2000 cm-1)、纤维素(1000-1100 cm-1)和木质素(1390-1420 cm-1)方面存在差异。总之,我们的数据表明,ATR-傅立叶变换红外光谱可用于不同植物物种中木质素和纤维素的相对定量。该方法成功地应用于绿豆茎细胞壁成分的快速筛选,同样也可用于其他作物或树种的筛选。
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来源期刊
Plant Methods
Plant Methods 生物-植物科学
CiteScore
9.20
自引率
3.90%
发文量
121
审稿时长
2 months
期刊介绍: Plant Methods is an open access, peer-reviewed, online journal for the plant research community that encompasses all aspects of technological innovation in the plant sciences. There is no doubt that we have entered an exciting new era in plant biology. The completion of the Arabidopsis genome sequence, and the rapid progress being made in other plant genomics projects are providing unparalleled opportunities for progress in all areas of plant science. Nevertheless, enormous challenges lie ahead if we are to understand the function of every gene in the genome, and how the individual parts work together to make the whole organism. Achieving these goals will require an unprecedented collaborative effort, combining high-throughput, system-wide technologies with more focused approaches that integrate traditional disciplines such as cell biology, biochemistry and molecular genetics. Technological innovation is probably the most important catalyst for progress in any scientific discipline. Plant Methods’ goal is to stimulate the development and adoption of new and improved techniques and research tools and, where appropriate, to promote consistency of methodologies for better integration of data from different laboratories.
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