Nakamura Lab/Bioinformatics Center  Department of Infection Metagenomics

Next-generation sequencing (NGS) is a technology that can generate enormous amount of genomic information in a short time and has made huge progress in genomic science and infectious disease research. At the Department of Infection Metagenomics specialists in bioinformatics, microbiology, and infectious diseases gather to conduct research on pathogens and infectious diseases using NGS-based genomic/metagenomic analysis.

Development of methods for pathogen detection based on metagenomic analysis

A metagenome is the sum of all genomes of all organisms inhabiting a particular environment. The emergence of NGS has enabled comprehensive analysis of genomic information from large numbers of organisms, thereby leading to significant advances in metagenomic analysis. For example, comprehensive analysis of microbial genomes in blood or nasopharyngeal samples from patients suffering from diseases of unknown cause makes it possible to identify the pathogens causing these symptoms and the genetic factors responsible for pathogenesis. This method, unlike conventional pathogen-specific methods, is applicable to various types of sample (e.g., blood, nasal swab, stool). It can also detect multiple pathogens in a single sample. Our laboratory uses metagenomic analysis to develop new methods for the diagnosis of infectious diseases.

Study of gut flora during onset of infectious disease

It is becoming clear that the gut microbiota is involved in various diseases and plays an important role in host defense. By performing metagenomic analysis of changes in and recovery of bacterial gut flora over time in cases of diarrhea, our laboratory is studying the relationship between human gut flora and pathogens. Furthermore, not only is bacterial gut flora related to disease, but it is also closely related to lifestyle factors. Our research is focused on how bacterial gut flora is affected by environmental factors and the physiological state of the individual.
NGS technology had made remarkable progress. New hardware platforms are being developed. NGS itself reads only nucleic acid sequences, and further analysis is
required to handle the enormous amount of data obtained. It is important to have a broad knowledge of bioinformatics, microbiology, and genomics in order to select the appropriate model based on the characteristics of each sequencing platform. At our laboratory, we carry out co-operative research with specialists in the fields of bioinformatics, microbiology, and infectious diseases.

Genomic analysis of microbial pathogens

The molecular mechanisms underlying the pathogenicity of many infectious diseases remain unclear. Our laboratory conducts genomic analysis-based research to identify genes responsible for pathogenicity and to identify the molecular mechanisms by which infectious diseases develop.

  • Fig. 1.Large scale computer system for NGS data analysis.

  • Fig. 2.Genomic analysis of Vibrio parahaemolyticus using four models of next-generation sequencer: ■454 GS Jr (Roche)、■IonPGM(Life Technologies)、■MiSeq(Illumina)、■Pacific Biosciences RS System (PacBio) GS Jr, MiSeq, and IonPGM produce short reads. Therefo

Staff

  • Assoc. Prof.: Shota Nakamura
  • Prof.: Tetsuya Iida (concur.)
  • Assoc. Prof.: Daisuke Motooka (concur.)
  • SA Asst. Prof.: Yuki Matsumoto
  • SA Asst. Prof.: Kiyoharu Fukushima (concur.)
  • Postdoc.: Hiroya Oki
  • Postdoc.: Yuko Imamura

Website

Publications

  • 1)Structural basis for the toxin-coregulated pilus-dependent secretion of Vibrio cholerae colonization factor. Oki H. et al., Sci Adv. (2022) 8(41):eabo3013
    2)Longitudinal alterations of the gut mycobiota and microbiota on COVID-19 severity. Maeda Y. et al., BMC Infect Dis. (2022) 22(1):572.
    3)Benchmark of 16S rRNA gene amplicon sequencing using Japanese gut microbiome data from the V1-V2 and V3-V4 primer sets. Kameoka S. et al., BMC Genomics (2021) 22(1):527.
    4)Pulmonary disease caused by a newly identified mycobacterium: Mycolicibacterium toneyamachuris: a case report. Kuge T. et al., BMC Infect Dis. (2020) 20(1):888
    5)Comprehensive subspecies identification of 175 nontuberculous mycobacteria species based on 7547 genomic profiles. Matsumoto Y. et al., Emerg Microbes Infect. (2019) 8(1):1043-1053.