Other issues to be urgently addressed.
Title of Research:
17_S05-01

Development of Novel Analytical System of Biological Responses toChemicals by Deep Phenotyping Method
Principal Investigator:
Hiroyuki Kusuhara (Professor, University of Tokyo, Graduate School of Pharmaceutical Sciences,
Department of Molecular Pharmacokinetics)
7-3-1 Hongo, Bunkyo, Tokyo, 113-0033, Japan(tel) +81-3-5841-4770, (e-mail) kusuhara@mol.f.u-tokyo.ac.jp
Collaborators:
Tadahaya Mizuno (Assistant Professor, University of Tokyo, Graduate School of PharmaceuticalSciences, Department of Molecular Pharmacokinetics)
7-3-1 Hongo, Bunkyo, Tokyo, 113-0033, Japan(tel) +81-3-5841-4771, (e-mail) tadahaya@mol.f.u-tokyo.ac.jp
Setsuo Kinoshita (Contract Research Student, University of Tokyo, Graduate School of
Pharmaceutical Sciences, Department of Molecular Pharmacokinetics)
7-3-1 Hongo, Bunkyo, Tokyo, 113-0033, Japan
Summary of Research:
Today, organisms are always exposed to chemicals in every situation to some extent. Widevariety of chemicals exist around us and the chemicals affect organisms not one by one but
simultaneously like a complex. The fact prompts us to care “multiple exposure”. To achieve theappropriate and correct prediction of multiple exposure of chemicals, it is necessary tocomprehend the effects of chemicals even if those are unknown and difficult to be detected. In thisstudy, we tackle with the theme by omic approaches with innovative techniques in both dataacquisition and data analysis method.
This study consists of two pillars: (1) a novel acquisition method of proteome profile data by
2-dimensional electrophoresis (2DE) and (2) a new analysis method of profile data, orthogonallinear separation analysis (OLSA). In this 7th term, the last term, we tested the performance of 2DE
in detection of chemical features and showed capacity of OLSA to uncover novel aspects of anatural product.
We have carried out 2DE of HeLa cells treated with 6 different anti-cancer drugs under several
conditions obtained total 33 proteome profile data. Clustering analysis revealed good separation ofeach drug group composed of three biological replicates except for Cisplatin and doxorubicin. Of
note, combinatorial treatment of a MEK1/2 inhibitor (PD184352) and a microtubule inhibitor(vincristine) constructed a specific cluster and OLSA successfully extracted the combinatorial
effect as a specific vector that was not observed in each inhibitor alone.
As for data analysis, we have extended our profile data analysis method to achieve fully unbiased
analysis by implementation of parallel analysis. This extension enabled us to estimate theappropriate number of effects to be decomposed, without existing body of biological knowledge. In
fact, the basic effects generated by the renewed method were well consistent with gene groups
defined in gene ontology, compared with the original one, when Gaussian noise were added to thedata. To test the performance of our decomposition analysis approach, Rescinnamine, a natural
product was subjected to OLSA. We detected four main effects of the natural product and two ofthem were actually confirmed in vitro analysis such as luciferase assay and western blotting
analysis. All of these data suggest that our platform has the potential to boost deep understandingof combinatorial exposure of chemicals.
Timeline:
March 1, 2019 - February 29, 2020
Topics:1. Poster presentation at JCIA LRI Annual Workshop 2019 “Development of Novel AnalyticalOther issues to be urgently addressed.
System of Biological Responses to Chemicals by Deep Phenotyping Method” (Tokyo, August30th, 2019)
Publications:
1. Akademi) ICCA-LRI workshop, June 19-20, 2019, Stresa, Italy
2. Journal) Kinoshita S, Biol Pharm Bull, 2019