Small compound-based direct cell conversion with combinatorial optimization of pathway regulations

Author:

Nakamura Toru1,Iwata Michio1,Hamano Momoko1,Eguchi Ryohei1,Takeshita Jun-ichi2,Yamanishi Yoshihiro1

Affiliation:

1. Department of Bioscience and Bioinformatics, Faculty of Computer Science and Systems Engineering, Kyushu Institute of Technology , Iizuka, Fukuoka 820-8502, Japan

2. Research Institute of Science for Safety and Sustainability, National Institute of Advanced Industrial Science and Technology (AIST) , Tsukuba, Ibaraki 305-8569, Japan

Abstract

Abstract Motivation Direct cell conversion, direct reprogramming (DR), is an innovative technology that directly converts source cells to target cells without bypassing induced pluripotent stem cells. The use of small compounds (e.g. drugs) for DR can help avoid carcinogenic risk induced by gene transfection; however, experimentally identifying small compounds remains challenging because of combinatorial explosion. Results In this article, we present a new computational method, COMPRENDRE (combinatorial optimization of pathway regulations for direct reprograming), to elucidate the mechanism of small compound-based DR and predict new combinations of small compounds for DR. We estimated the potential target proteins of DR-inducing small compounds and identified a set of target pathways involving DR. We identified multiple DR-related pathways that have not previously been reported to induce neurons or cardiomyocytes from fibroblasts. To overcome the problem of combinatorial explosion, we developed a variant of a simulated annealing algorithm to identify the best set of compounds that can regulate DR-related pathways. Consequently, the proposed method enabled to predict new DR-inducing candidate combinations with fewer compounds and to successfully reproduce experimentally verified compounds inducing the direct conversion from fibroblasts to neurons or cardiomyocytes. The proposed method is expected to be useful for practical applications in regenerative medicine. Availability and implementation The code supporting the current study is available at the http://labo.bio.kyutech.ac.jp/~yamani/comprendre. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

JSPS KAKENHI

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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