Probing the Metabolic Landscape of Plant Vascular Bundles by Infrared Fingerprint Analysis, Imaging and Mass Spectrometry.
André GündelAlexander HiloHardy RolletschekLjudmilla BorisjukPublished in: Biomolecules (2021)
Fingerprint analysis is a common technique in forensic and criminal investigations. Similar techniques exist in the field of infrared spectroscopy to identify biomolecules according to their characteristic spectral fingerprint features. These unique markers are located in a wavenumber range from 1800 to 600 cm-1 in the mid infrared region. Here, a novel bioanalytical concept of correlating these spectral features with corresponding mass spectrometry datasets to unravel metabolic clusters within complex plant tissues was applied. As proof of concept, vascular bundles of oilseed rape (Brassica napus) were investigated, one of the most important and widely cultivated temperate zone oilseed crops. The link between mass spectrometry data and spectral data identified features that co-aligned within both datasets. Regions of origin were then detected by searching for these features in hyperspectral images of plant tissues. This approach, based on co-alignment and co-localization, finally enabled the detection of eight distinct metabolic clusters, reflecting functional and structural arrangements within the vascular bundle. The proposed analytical concept may assist future synergistic research approaches and may lead to biotechnological innovations with regard to crop yield and sustainability.
Keyphrases
- mass spectrometry
- liquid chromatography
- optical coherence tomography
- high resolution
- gene expression
- high performance liquid chromatography
- capillary electrophoresis
- electronic health record
- climate change
- deep learning
- rna seq
- computed tomography
- magnetic resonance imaging
- single cell
- magnetic resonance
- convolutional neural network
- artificial intelligence
- drug delivery
- data analysis
- quantum dots
- current status