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

Author:

Pezzotti Giuseppe1234567ORCID,Tsubota Yusuke1,Zhu Wenliang1ORCID,Marin Elia14ORCID,Masumura Takehiro8,Kobayashi Takuya9,Nakazaki Tetsuya10

Affiliation:

1. Ceramic Physics Laboratory, Kyoto Institute of Technology, Sakyo-ku, Matsugasaki, Kyoto 606-8585, Japan

2. Department of Molecular Genetics, Institute of Biomedical Science, Kansai Medical University, 2-5-1 Shinmachi, Hirakata, Osaka 573-1010, Japan

3. Department of Immunology, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, 465 Kajii-cho, Kyoto 602-8566, Japan

4. Department of Dental Medicine, Graduate School of Medical Science, Kyoto Prefectural University of Medicine, Kamigyo-ku, Kyoto 602-8566, Japan

5. Department of Orthopedic Surgery, Tokyo Medical University, 6-7-1 Nishi-Shinjuku, Shinjuku-ku, Tokyo 160-0023, Japan

6. Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy

7. Department of Molecular Science and Nanosystems, Ca’ Foscari University of Venice, Via Torino 155, 30172 Venice, Italy

8. Laboratory of Genetic Engineering, Kyoto Prefectural University, 1-5 Shimogamohangi-cho, Sakyo-ku, Kyoto 606-8522, Japan

9. Department of Medical Chemistry, Kansai Medical University, 2-5-1 Shinmachi, Osaka Prefecture, Hirakata 573-1010, Japan

10. Experimental Farm, Graduate School of Agriculture, Kyoto University, Kizugawa 619-0218, Japan

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.

Publisher

MDPI AG

Subject

Plant Science,Health Professions (miscellaneous),Health (social science),Microbiology,Food Science

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