Data-Driven Characterization of Metabolome Reprogramming during Early Development of Sorghum Seedlings.
Ian A DuberyLerato P NephaliFidele TugizimanaPaul A SteenkampPublished in: Metabolites (2024)
Specialized metabolites are produced via discrete metabolic pathways. These small molecules play significant roles in plant growth and development, as well as defense against environmental stresses. These include damping off or seedling blight at a post-emergence stage. Targeted metabolomics was followed to gain insights into metabolome changes characteristic of different developmental stages of sorghum seedlings. Metabolites were extracted from leaves at seven time points post-germination and analyzed using ultra-high performance liquid chromatography coupled to mass spectrometry. Multivariate statistical analysis combined with chemometric tools, such as principal component analysis, hierarchical clustering analysis, and orthogonal partial least squares-discriminant analysis, were applied for data exploration and to reduce data dimensionality as well as for the selection of potential discriminant biomarkers. Changes in metabolome patterns of the seedlings were analyzed in the early, middle, and late stages of growth (7, 14, and 29 days post-germination). The metabolite classes were amino acids, organic acids, lipids, cyanogenic glycosides, hormones, hydroxycinnamic acid derivatives, and flavonoids, with the latter representing the largest class of metabolites. In general, the metabolite content showed an increase with the progression of the plant growth stages. Most of the differential metabolites were derived from tryptophan and phenylalanine, which contribute to innate immune defenses as well as growth. Quantitative analysis identified a correlation of apigenin flavone derivatives with growth stage. Data-driven investigations of these metabolomes provided new insights into the developmental dynamics that occur in seedlings to limit post-germination mortality.
Keyphrases
- plant growth
- ms ms
- mass spectrometry
- innate immune
- arabidopsis thaliana
- ultra high performance liquid chromatography
- tandem mass spectrometry
- big data
- liquid chromatography
- electronic health record
- coronary artery disease
- amino acid
- high performance liquid chromatography
- risk assessment
- human health
- type diabetes
- cardiovascular events
- machine learning
- high resolution
- fatty acid
- gas chromatography
- artificial intelligence