Development of Technology to Analyze Antibiotic Resistance Mutations in Ribosomal RNAs

– For the construction of a resistance mutation database useful for early detection of resistant bacteria –

Researcher: Kentaro Miyazaki, Leader, Synthetic Bioengineering Research Group, Bioproduction Research Institute


  • Applied the AIST original ribosomal RNA (rRNA) functional analysis technology to screening for antibiotic resistance
  • Discovered new antibiotic resistance mutations in 16S rRNAs from environmental bacteria
  • Expected to be used for constructing a database of new resistance mutations against various antibiotics

Social Background of Research

Although antibiotics are efficient at killing pathogenic bacteria, many of them are capable of acquiring resistance and evade antibiotic attacks, which is a serious social problem worldwide. However, our knowledge of resistance mutations, which are important for early detection and diagnosis of resistant bacteria, is still fragmental. One of the reasons for the insufficient information is the lack of an adequate approach to functional analysis of rRNAs, which are the major target of many antibiotics.


The researcher, in collaboration with Hokkaido University, has discovered multiple 16S rRNA genes that demonstrate resistance to spectinomycin, an antibiotic used to treat gonorrhea infections, from 16S rRNA gene libraries of environmental bacteria. Subsequent mutational analysis of the resistance genes has resulted in the discovery of new resistance mutations.

rRNAs are one of the main targets of antibiotics, so when resistance mutations occur in rRNAs, antibiotics would not work. Therefore, information on resistance mutations is useful for early detection of resistant bacteria. However, it has long been difficult to identify such resistance mutations in rRNAs. In this research, the researcher at AIST applied the AIST original technology for functional analysis of 16S rRNA from diverse array of bacteria using Escherichia coli as a host to explore antibiotic resistance mutations in environmental bacteria. As the result, the researcher has identified 4 spectinomycin resistant 16S rRNA genes from environmental bacteria. Also, he discovered 3 new resistance mutations therein. By applying this method to various antibiotics, it is expected that we can establish a database of resistance mutations, which should be useful for finding and diagnosing resistant bacteria.

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