Microbial Genomics; Environmental Bioinformatics
“Advanced Biosciences” seminars (Tomita, Naito, Kuroda, Kanai, Soga, Arakawa, Suzuki and Tsujimoto) are operated along with “Systems Biology Project” for graduate students. All members, including faculty members, graduate students, and undergraduate students are involved to research projects.
At the first semester when you join the "Advanced Biosciences" seminars (Kenkyukai), you should take "SEMINAR B (1) Masaru Tomita."
Please check our website for more details. https://bio.sfc.keio.ac.jp/
While microorganisms have important roles in various environments (e.g. human body, natural and built environments), they can cause many infectious diseases, which are threats to public health. In this research group, we use bioinformatics and genomics to understand microbial diversity and its medicinal, agricultural and industrial applications.
Our research focuses on reproducible bioinformatics, genome microbiology, and urban microbiomes. It has been estimated that, by 2050, 10 million people will die every year due to antimicrobial resistance (AMR) if no action is taken. Plasmids often carry multiple AMR genes and can be horizontally transferred between microbes, contributing to the spread of AMR in microbial communities. To identify and track antimicrobial resistance genes (resistomes) and mobile genetic elements (e.g., viruses, plasmids, and transposable elements) in urban built environments, we have been collecting samples in mass-transit systems around the globe (Danko et al., 2020) and will sample urban environments around the globe before, during and after the COVID-19 pandemic and the mass gathering such as international sport events including the World Cup and Olympic & Paralympic Games (http://metasub.org/projects/). We are using a combination of bioinformatics tools for creating global maps of microbiomes and resistomes, inferring host range and transmission routes of mobile genetic elements (e.g., viruses and plasmids), and gaining insight into microbial lifestyles (Yano et al., 2018; Merino et al., 2019; Tokuda et al., 2020).