Based on the conventional nutritional study, sugar, protein, lipids were independently considered in several diseases, including cancer and metabolic diseases. However, recent researches in cancer and metabolic diseases have been dramatically improved our metabolic knowledge of these disorders due to latest understanding of nutritional study. Indeed, sugar, protein, lipids are inter-connected in the metabolic pathways, through the several key metabolic molecules such as acetyl-CoA and ketone body intermediates partly under epigenetic regulation. Our group reported that several key regulators in metabolic diseases such as Atherosclerosis. We also reported that hypoxia, nutrient starvation, acidic pH may induce tumor aggressiveness by epigenetic regulation in cancer cells. We found that epigenetic and metabolic changes influence development of cancer and metabolic diseases associated with life span from infant, through growth phase to adult phase, that can be utilizes for the development of novel therapies by integration of genome, epigenome, transcript, proteome, metabolome data analysis. Our challenges include: (1) Regulation of novel onco-metabolites (cancer associated metabolites) for the treatment of cancer. (2) Regulation of starvation and negative energy balance for the treatment of metabolic diseases. (3) Latest understanding of metabolism for treatment of these disorders. We challenge to develop therapeutics for advanced metabolic cancer, diabetes, atherosclerosis, osteoporosis, and muscle weakness, improvement of the aged basal metabolism through integration of epigenome and metabolome analysis.
We are working with systems biology and medicine to understand complex biological systems through a functional genomics approach. High throughput technology and novel algorithms are required for collecting, integrating and visualizing the enormous amount of data on gene expression, protein expression, and protein interactions arising in the wake of the Human Genome Project. Alliance with external academics and industry will be crucial to the success of the new "systems biology", that is, understanding biological systems as more than the sum of their parts.
Aburatani Lab (Genome Science)
Aburatani Lab (Genome Science)
Epigenome such as DNA methylation and histone modifications is acquired genetic infomation that is rewritable via various enviromental cues. Epigenome is cellular memory for adapting to the external environment, and it is closely involved in disease onset. Under the concept of "neo-nutritional science", we are integrally analyzing transcriptome, epigenome, and metabolome in adipocytes to reveal environmental adaptation system, and will build up a new paradigm for lifestyle-related disease.
Sakai Lab (Metabolic Medicine)
Sakai Lab (Metabolic Medicine)
How do our bodies develop from single fertilized egg cells? How does its cell lineage look like? How many cell divisions do cells in each organ experience? How does a malignant tumour progress by interacting with mutated genome and cellular niches? What kind of different molecular networks do contribute to different cellular phenotypes? Almost all of the big challenges in current life science involve high-resolution understanding of heterogeneous molecular and cellular dynamics in multicellular organisms. To enable to answer these questions, we develop genetic circuits harnessing the idea of tagging molecules and cells with DNA barcodes, genome editing and computational data mining.
Yachie Lab (Synthetic Biology Division)
Yachie Lab (Synthetic Biology Division)
Because of recent advance in supercomputer it is getting possible to perform molecular dynamics (MD) simulations of biomolecules such as protein, DNA, and RNA after building up accurate molecular models based on quantum mechanics. Using high-level quantum mechanical theory we are developing more accurate unified force field than traditional ones. Using nonequilibrium Jarzynski identity we developed massively parallel computational method of binding free energy (MPCAFEE), which made it possible to quantitatively compare the calculated binding free energies with experimental binding constants commonly measured in the drug development. Recently we have succeeded to improve the accuracy of DNA and lipid force field in consistent way with the protein force field. We will continue the research to make concrete physical basis for the life science.
By using theoretical and computational methods, we study properties and functions of complexes and assemblies (supramolecules) of biological molecules at the atomic/molecular level. In particular, accurate analyses of structures/dynamics/energetics are performed based on the quantum chemistry and the molecular dynamics methods. We aim not only to understand/predict phenomena but also to develop new theoretical analysis methods and computational algorithms. Furthermore, we aim to apply these to drug design and material design.
The number of hypertensive and diabetic patients reaches 40 and 9.5 million in Japan. Despite the development of many anti-hypertensive and –diabetic drugs, the number of cardiovascular disease and chronic kidney disease keeps increasing. Epigenetic abnormalities may underlie hypertension and diabetic kidney disease. Epigenetics, a switching mechanism involved in regulation of gene expression by DNA methylation and histone modifications, controls memory of the cells. We are trying to find new diagnostic and therapeutic approaches by targeting epigenetic abnormalities.
Based on the conventional nutritional notion, carbohydrates, lipids and amino acids were independently considered in cancer. However, recent researches in cancer metabolism have been dramatically improved our metabolic knowledge of these disorders due to latest understanding of cancer metabolism. Indeed, carbohydrates, lipids and amino acids are inter-connected in the metabolic pathways, through the several key metabolic molecules such as acetyl-CoA and ketone body intermediates partly under epigenetic regulation. Our group reported that hypoxia, nutrient starvation, acidic pH may induce tumor aggressiveness by epigenetic regulation in cancer cells. We found that epigenetic and metabolic changes influence cancer progression, that can be utilizes for the development of novel therapies by integration of genome, epigenome, transcriptome, proteome, metabolome analysis.Our research objectives: (1)To identify novel onco-metabolites (cancer associated metabolites) for the treatment of cancer. (2)To understand the mechanism of cancer adaptation in carbohydrate/lipids/amino acids deficiency and apply it to therapy. (3)Latest understanding of “nutriomics” for treatment of cancer. We challenge to develop therapeutics for metastasis and recurrent advanced cancer through the viewpoint of integrative “multiomics” approach.
Trans-disciplinary science by networking biological measurements With strong and widely spread expertise in optics, microfluidics, material synthesis, genomics, and engineering, we develop physical tools to probe biological structures and realize ways to network biological measurements for interrogating complex life systems. By fusing our strength with the power of information science, we tackle fundamental problems in biophysical and biological science, and explore the potential of such studies in healthcare industry. Ultimately, we aim at creating a machine that thinks by itself to discover something crazy with biology, physics and medicine outlooks. Develop bioimaging/sensing, micro/nanofluidics, and information technologies To these grand challenges and independently, we actively work on development of novel optical imaging, functional micro/nanofluidics, and information techniques, and their integrated modalities. Along such scientific explorations, new technologies continually emerge and may spin out to create industrial activities with further excitement. Welcome applicants who are interested to study experimental optics, microfluidics, biophysics, information- and bio-technologies, and/or to create values by combining these disconnected technologies.
With the development of sequencing technology, electronic data yields in biology have been steadily increasing, and it is already a challenging task to process large volumes of data in a conventional method. In addition, in order to extract knowledge from multi modal big data, (ex. Multi-omics data) it is necessary to incorporate the latest Data Science technology, such as cloud computing and machine learning. Research topics include following. 1. Epitranscriptome analysis Epitranscriptome is transcriptomics with biochemical modifications of RNA. In previous studies, we have developed a bioinformatics method to comprehensively detect inosine-modified sites in the transcriptome at the base level. 2. Cancer genomics With using next generation sequencer (NGS), it became feasible to detect cancer somatic mutations comprehensively, and NGS is now used as clinical applications, in additions to a research use. Because the allelic fraction of a mutation depends on the tumor purity, local copy number and clonality, it is sometime difficult to call somatic mutation with high accuracy with different specimen. In previous studies, we developed algorithms to calculate somatic mutations, copy number mutations and tumor rates in cancer cells even under noisy low tumor purity conditions. 3. Bioinformatics data analysis using Data Science In order to find the biological knowledge from biological big data, it is necessary to aggregate data on a cloud and perform distributed processing. We are developing cloud based NGS analysis pipeline using Hadoop / Spark , popular cloud computing framework, and deep learning library. Hepatitis B Virus (HBV) integration sites (blue) and DNA copy number break points (red) on human genome RNA Sequencing and Whole genome sequencing using Hadoop