Raman Multi-Omic Snapshots of Koshihikari Rice Kernels Reveal Important Molecular Diversities with Potential Benefits in Healthcare

Abstract

This study exploits quantitative algorithms of Raman spectroscopy to assess, at the molecular scale, the nutritional quality of individual kernels of the Japanese short-grain rice cultivar Koshihikari in terms of amylose-to-amylopectin ratio, fractions of phenylalanine and tryptophan aromatic amino acid residues, protein-to-carbohydrate ratio, and fractions of protein secondary structures. Statistical assessments on a large number of rice kernels reveal wide distributions of the above nutritional parameters over nominally homogeneous kernel batches. This demonstrates that genetic classifications cannot catch omic fluctuations, which are strongly influenced by a number of extrinsic factors, including the location of individual grass plants within the same rice field and the level of kernel maturation. The possibility of collecting nearly real-time Raman “multi-omic snapshots” of individual rice kernels allows for the automatic (low-cost) differentiation of groups of kernels with restricted nutritional characteristics that could be used in the formulation of functional foods for specific diseases and in positively modulating the intestinal microbiota for protection against bacterial infection and cancer prevention.

Keywords

• Raman spectroscopy
• rice kernels
• metabolites
• molecular structure
• statistical distributions