1. Development of genome engineering technology

Genome engineering technology, by which several tens to hundreds of genes can be manipulated at the same time based on genome information, is a key technology for modifying bacterial traits rationally.

Our research group has developed genome engineering technologies for modifying Corynebacterium glutamicum that is expected to be a useful platform for the industrial production of various compounds. By analysis of the C. glutamicum genome we have obtained genome-wide information such as non-essential genes identified, which is useful for metabolic engineering. By some genetic engineering techniques newly developed, we can delete several tens of genes or introduce a number of genes into the genome at the same time. We can also introduce/delete a number of genes without using selection markers such as antibiotics the use of which is not desirable in industrial production processes.

2. Development of gene expression system

Our research group has developed plasmid vector systems and inducible promoters, which enables examining optimal expression levels of genes in metabolic engineering of Corynebacterium glutamicum efficiently. We have also developed a protein secretion system.

We isolated two new plasmids, and constructed total 42 plasmid vectors compatible in a C. glutamicum cell by using six plasmids (the new plasmids and four ones previously isolated) along with seven antibiotic resistance genes. We also modified the copy number of the vector plasmids from several tens to hundreds. Furthermore, we introduced random mutations in the new plasmid and screened for a temperature-sensitive plasmid that enables efficient genetic engineering of the C. glutamicum chromosome.

We established gene expression systems under the control of various promoters identified based on transcriptome analysis.

3. Genome analysis

Our research group has determined the entire genome sequences of Desulfitobacterium hafniense Y51, and Clostidium kluyveri. in addition to Corynebacterium glutamicum R. It is estimated that the 5.7-Mbp chromosome of D. hafniense Y51 encodes 5060 ORF. Although the genome of D. hafniense Y51 is larger than that of other dehalogenating bacterial species such as D. ethenogenes 195, only two homologs of dehlogenase genes is found on the former genome. In contrast, it is interesting to note that many genes supposed to be involved in electron transfer are present on the D. hafniense Y51 genome. Clostridium kluyveri was isolated as an anaerobe producing caproate (C6) and butyrate (C4) from ethanol (C2) and acetate (C2). Its genome sequence determined will be published in future.

4. Transcriptome analysis

Our research group analyzes transcriptomes of the microbial cells under various conditions by using the DNA microarray carrying 99.9% of all the genes on the genome of Corynebacterium glutamicum R.

A transcription factor binds to the promoter region of the target gene, thereby activating or repressing its expression. ChIP-chip analysis elucidates the binding regions on the chromosome, thereby identifying the multiple target genes, if any, under the direct control of a transcription factor of interest. A consensus sequence recognized by a transcription factor is also identified. The ChIP-chip data combined with transcriptome data of a mutant deficient in the transcription factor elucidates whether the factor acts as an activator or a repressor of its respective target genes.

5. Metabolome analysis

　The recent advance in instruments for chemical analyses such as liquid chromatography, gas chromatography, and mass spectrometry, along with the great improvement of computational capability enables metabolome analysis identifying many intracellular metabolites at the same time. Our research group uses the metabolome analysis technology in metabolic engineering for the development of higher efficient bioprocesses.

6. Metagenome analysis

Metagenome analysis identifies a gene of interest amplified by PCR from an environmental sample. This technology has recently been applied for analysis of microbial population in an ecosystem. Thus far, our research group has analyzed high-depth underground ecosystems such as an oil well and natural gas well.