NAIST Division of Biological Science

Laboratories and faculty

Bioengineering

BS CB BN DS

Outline of Research and Education

To contribute to society through biotechnology, we are developing basic technologies for high production of useful proteins such as biopharmaceuticals in plants, by understanding the mechanism of gene expression regulation of plants.

We provide guidance so that the students assigned to the laboratory can understand the research logically and broaden and develop the base of knowledge. In addition to regular laboratory meetings, we invite researchers and practitioners from industry to introduce the knowledge necessary for research and development in companies. Through these guidance, we aim to develop human resources who can play an active role in a low-growth, global society.

Major Research Topics

Isolation and improvement of elements involved in high expression of transgene

Gene expression in cells is regulated in processes such as transcription, post-transcription, and translation. In order to efficiently express useful genes introduced into plants, it is necessary to optimize each process. Therefore, we are analyzing the core promoter involved in transcription, the terminator involved in transcription termination and mRNA processing, the splicing mechanism involved in mRNA diversity, the analysis of internal cleavage sites related to mRNA stability, and translation efficiency. Through these analyzes, we are isolating and improving the sequence elements involved in high expression. We also aim to provide the results obtained to multiple companies to produce vaccine proteins and growth hormones in plants (Fig. 1)

Design of artificial gene

The gene expression control differs for each gene, but this difference can be explained by the difference in sequence or sequence-dependent structure. For example, translation efficiency also differs for each gene. We have obtained translation status data of all mRNAs and sequence data of all mRNAs. By performing in silico analysis using two genome-wide data, we are constructing a machine learning model that can predict the translation efficiency from mRNA to protein. By utilizing this machine learning model, in addition to further understanding of the gene expression control mechanism, it is possible to select the 5'UTR sequence that enables high translation of the target gene. In addition, we are constructing a machine learning model using comprehensive intracellular data on transcription initiation sites /splicing patterns /poly A addition sites. Ultimately, we would like to utilize these machine learning models to design artificial genes that enable higher expression (Fig. 2)

Fig. 1
Fig.1 Flow of gene expression
In order to optimize each step of gene expression, we analyze each regulatory process in detail and isolate and improve sequence elements involved in high expression of transgene.
Fig. 2
Fig.2 Design of artificial gene
In addition to mRNA translation status analysis and stability analysis, we will construct a machine learning model using comprehensive intracellular data on transcription initiation sites / splicing patterns / poly A addition sites. Ultimately, we will design artificial genes that can optimize the expression of useful genes.

References

  1. Ueno D. et al., Plant Cell Physiol., in press, 2020
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  7. Yamasaki S. et al., Plant Cell Physiol., 56, 2069-2180, 2015
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  10. Matusi T. et al., Plant Biotechnol., 31, 191-194, 2014