We isolate and culture microorganisms, which are materials for research, using various methods. The isolated microbial strains are then characterized by a polyphasic taxonomic approach using various methods. As a result, if it is judged to be a new species, the species is described, and a new scientific name is proposed. It’s a simple process, but I think it’s often confusing for the first time. In this paper, I would like to explain the tips and points to be aware of to proceed with these processes smoothly.

In order to handle microorganisms safely, it is necessary to know in advance the risk of the microorganisms to be used. In recent years, with the rapid development of next-generation DNA sequencing technology, there has been a requirement to assess the estimation of safety at the gene level based on genome sequences. In addition, since the application of whole genome sequences to microbial classification is progressing, microbial taxa are being reclassified and scientific names are being changed. In order to support the safe and appropriate use of microorganisms, NITE has developed “MiFuP Safety”, a tool for detecting potential genes involved in toxins and other functions with risks from genome sequences. We also provide the database “the Microorganism Risk Information List”, that organizes the latest scientific names and centralizes information on biosafety levels and domestic regulations related to handling of microorganisms. This paper describes the background and usage of these tools and databases, and introduces the recent renewal of these databases.

Safety is one of the most important values and is defined as “freedom from unacceptable risk”. Products and services provided to society require safety, convenience and economy, however, they are trade-offs, and it is the role of scientists (engineers and researchers) to seek a better balance between them. To this end, it is necessary to act assuming that when we cannot be sure that it is safe, it is dangerous. It must also take into account the diversity of people’s values of safety and that the level of risk they can accept depends on whether it is a voluntary act or not. Laws and rules are an afterthought, whereas scientists emphasize novelty and pioneer a world without rules. They are therefore responsible for anticipating and avoiding the various problems that may arise when implementing the knowledge and conveniences obtained in society. Furthermore, they are responsible for proposing the rules necessary for this, which requires an ethical awareness at the post-conventional level as described by Kohlberg. Contributing to the safety and security of society fulfils the most important requirement for well-being and leads to the well-being of our scientists themselves.

RNA-seq is a tool for measuring gene expression and is commonly used for identifying differentially expressed genes (DEGs) under different conditions or groups. Most of the programs for DEGs has been provided as a free software environment called R. Users typically start the analysis with a numerical matrix called “count data”, where each row a gene, each column a sample (a group’s replicate), and each cell the number of counts. We describe the characteristics of the count data with a scatter plot (so-called “mean-variance plot”) displaying the relationship between the mean (x-axis) and variance (y-axis) within replicates. We explain why a statistical model called the negative binomial distribution (NB model) has been used for identifying DEGs.