Michihiro Tanaka

Precise correction of the dystrophin gene in duchenne muscular dystrophy patient induced pluripotent stem cells by TALEN and CRISPR-Cas9.

Summary Duchenne muscular dystrophy (DMD) is a severe muscle-degenerative disease caused by a mutation in the dystrophin gene. Genetic correction of patient-derived induced pluripotent stem cells (iPSCs) by TALENs or CRISPR-Cas9 holds promise for DMD gene therapy; however, the safety of such nuclease treatment must be determined. Using a unique k-mer database, we systematically identified a unique target region that reduces off-target sites. To restore the dystrophin protein, we performed three correction methods (exon skipping, frameshifting, and exon knockin) in DMD-patient-derived iPSCs, and found that exon knockin was the most effective approach. We further investigated the genomic integrity by karyotyping, copy number variation array, and exome sequencing to identify clones with a minimal mutation load. Finally, we differentiated the corrected iPSCs toward skeletal muscle cells and successfully detected the expression of full-length dystrophin protein. These results provide an important framework for developing iPSC-based gene therapy for genetic disorders using programmable nucleases.

KEGG OC: a large-scale automatic construction of taxonomy-based ortholog clusters

The identification of orthologous genes in an increasing number of fully sequenced genomes is a challenging issue in recent genome science. Here we present KEGG OC (http://www.genome.jp/tools/oc/), a novel database of ortholog clusters (OCs). The current version of KEGG OC contains 1 176 030 OCs, obtained by clustering 8 357 175 genes in 2112 complete genomes (153 eukaryotes, 1830 bacteria and 129 archaea). The OCs were constructed by applying the quasi-clique-based clustering method to all possible protein coding genes in all complete genomes, based on their amino acid sequence similarities. It is computationally efficient to calculate OCs, which enables to regularly update the contents. KEGG OC has the following two features: (i) It consists of all complete genomes of a wide variety of organisms from three domains of life, and the number of organisms is the largest among the existing databases; and (ii) It is compatible with the KEGG database by sharing the same sets of genes and identifiers, which leads to seamless integration of OCs with useful components in KEGG such as biological pathways, pathway modules, functional hierarchy, diseases and drugs. The KEGG OC resources are accessible via OC Viewer that provides an interactive visualization of OCs at different taxonomic levels.

Oil Accumulation by the Oleaginous Diatom Fistulifera solaris as Revealed by the Genome and Transcriptome

F. solaris has an allodiploid genome structure, and activation of lipid accumulation and degradation metabolism pathways at the same time might underlie its simultaneous growth and oil accumulation. Oleaginous photosynthetic organisms such as microalgae are promising sources for biofuel production through the generation of carbon-neutral sustainable energy. However, the metabolic mechanisms driving high-rate lipid production in these oleaginous organisms remain unclear, thus impeding efforts to improve productivity through genetic modifications. We analyzed the genome and transcriptome of the oleaginous diatom Fistulifera solaris JPCC DA0580. Next-generation sequencing technology provided evidence of an allodiploid genome structure, suggesting unorthodox molecular evolutionary and genetic regulatory systems for reinforcing metabolic efficiencies. Although major metabolic pathways were shared with nonoleaginous diatoms, transcriptome analysis revealed unique expression patterns, such as concomitant upregulation of fatty acid/triacylglycerol biosynthesis and fatty acid degradation (β-oxidation) in concert with ATP production. This peculiar pattern of gene expression may account for the simultaneous growth and oil accumulation phenotype and may inspire novel biofuel production technology based on this oleaginous microalga.

Analysis of a lipid biosynthesis protein family and phospholipid structural variations.

Glycerophospholipids are major structural lipids in cellular membrane systems and play key roles as suppliers of the first and second messengers in the signal transduction and molecular recognition processes. The distribution of lipid components differs among organelles and cells. The distribution is controlled by two pathways in lipid metabolism: de nova and remodeling pathways. Glycerophospholipids including arachidonic and stearic acids are mostly produced in the remodeling pathway, whereas lipid chains are reconstructed from those synthesized in the de novo pathway. Recently lysophospholipid acyltransferases have been isolated as key enzymes in the remodeling pathway, and the substrate specificity has been investigated in terms of the chemical substructures of glycerophospholipids, such as the type of head groups and the length of aliphatic chains. These experimental studies have been reported for specific organisms, and only two representative sequence motifs are known for acyltransferases: a general pattern and the pattern for membrane-bound O-acyltransferase (MBOAT). Here we attempt to correlate the sequence patterns and the substrate specificity of lysophospholipid acyltransferases in 89 eukaryotic genomes in order to understand the roles of this enzyme family and underlying glycerophospholipid structural variations. Using phylogenetic and domain analyses, the lysophospholipid acyltransferase family was divided into 18 subtypes. Furthermore, we examined the occurrence of identified subtypes in eukaryotic genomes, and found the expansion of these subtypes in vertebrates. These findings may provide clues to understanding structural variations and distributions of glycerophospholipids in different organisms.

Phylogenetic analysis of lipid mediator GPCRs.

Lipid mediator is the collective term for prostanoids, leukotrienes, lysophospholipids, platelet-activating factor, endocannabinoids and other bioactive lipids, that are involved in various physiological functions including inflammation, immune regulation and cellular development. They act by binding to their ligand-specific G-protein coupled receptors (GPCRs). Since 1990s a number of lipid GPCRs have been cloned in humans, with a few more identified in other vertebrates. However, the conservation of these receptors has been poorly investigated in other eukaryotes. Herein we performed a phylogenetic analysis by collecting their orthologs in 13 eukaryotes with complete genomes. The analysis shows that orthologs for prostanoid receptors are likely to be conserved in the 13 eukaryotes. In contrast, those for lysophospholipid and cannabinoid receptors appear to be conserved only in vertebrates and chordates. Receptors for leukotrienes and other bioactive lipids are limited to vertebrates. These results indicate that the lipid mediators and their receptors have coevolved with the development of highly modulated physiological functions such as immune regulation and the formation of the central nervous system. Accordingly, examining the presence and role of lipid mediator GPCR orthologs in invertebrate species can provide insight into the development of fundamental biological processes across diverse taxa.

Human AK2 links intracellular bioenergetic redistribution to the fate of hematopoietic progenitors

AK2 is an adenylate phosphotransferase that localizes at the intermembrane spaces of the mitochondria, and its mutations cause a severe combined immunodeficiency with neutrophil maturation arrest named reticular dysgenesis (RD). Although the dysfunction of hematopoietic stem cells (HSCs) has been implicated, earlier developmental events that affect the fate of HSCs and/or hematopoietic progenitors have not been reported. Here, we used RD-patient-derived induced pluripotent stem cells (iPSCs) as a model of AK2-deficient human cells. Hematopoietic differentiation from RD-iPSCs was profoundly impaired. RD-iPSC-derived hemoangiogenic progenitor cells (HAPCs) showed decreased ATP distribution in the nucleus and altered global transcriptional profiles. Thus, AK2 has a stage-specific role in maintaining the ATP supply to the nucleus during hematopoietic differentiation, which affects the transcriptional profiles necessary for controlling the fate of multipotential HAPCs. Our data suggest that maintaining the appropriate energy level of each organelle by the intracellular redistribution of ATP is important for controlling the fate of progenitor cells.

Microarray analyses of otospheres derived from the cochlea in the inner ear identify putative transcription factors that regulate the characteristics of otospheres

Various tissues possess tissue-specific stem/progenitor cells, including the inner ears. Stem/progenitor cells of the inner ear can be isolated as so-called otospheres from differentiated cells using a sphere forming assay. Although recent studies have demonstrated the characteristics of otospheres to some extent, most of the features of these cells are unknown. In this report, we describe the findings of transcriptome analyses with a cDNA microarray of otospheres derived from the cochleae of the inner ears of neonatal mice in order to clarify the gene expression profile of otic stem/progenitor cells. There were common transcription factors between otospheres and embryonic stem cells, which were supposed to be due to the stemness of otospheres. In comparison with the cochlear sensory epithelium, the otospheres shared characteristics with the cochlea, although several transcription factors specific for otospheres were identified. These transcription factors are expected to be essential for maintaining the characteristics of otospheres, and appear to be candidate genes that promote the direct conversion of cells into otic stem/progenitor cells.

Tracking Difference in Gene Expression in a Time-Course Experiment Using Gene Set Enrichment Analysis

Fistulifera sp. strain JPCC DA0580 is a newly sequenced pennate diatom that is capable of simultaneously growing and accumulating lipids. This is a unique trait, not found in other related microalgae so far. It is able to accumulate between 40 to 60% of its cell weight in lipids, making it a strong candidate for the production of biofuel. To investigate this characteristic, we used RNA-Seq data gathered at four different times while Fistulifera sp. strain JPCC DA0580 was grown in oil accumulating and non-oil accumulating conditions. We then adapted gene set enrichment analysis (GSEA) to investigate the relationship between the difference in gene expression of 7,822 genes and metabolic functions in our data. We utilized information in the KEGG pathway database to create the gene sets and changed GSEA to use re-sampling so that data from the different time points could be included in the analysis. Our GSEA method identified photosynthesis, lipid synthesis and amino acid synthesis related pathways as processes that play a significant role in oil production and growth in Fistulifera sp. strain JPCC DA0580. In addition to GSEA, we visualized the results by creating a network of compounds and reactions, and plotted the expression data on top of the network. This made existing graph algorithms available to us which we then used to calculate a path that metabolizes glucose into triacylglycerol (TAG) in the smallest number of steps. By visualizing the data this way, we observed a separate up-regulation of genes at different times instead of a concerted response. We also identified two metabolic paths that used less reactions than the one shown in KEGG and showed that the reactions were up-regulated during the experiment. The combination of analysis and visualization methods successfully analyzed time-course data, identified important metabolic pathways and provided new hypotheses for further research.

The impact of collapsing data on microarray analysis and DILI prediction

In this work, we focus on two fundamental problems of toxicogenomics using the data provided by the Japanese toxicogenomics project. First, we analyze to what extent animal studies can be replaced by in in vitro assays. We show that the probeset-level representation achieves poor agreement between in vivo and in vitro data. We present a data collapsing approach to resolve poor data agreement between in vivo and in vitro data, as measured by GSEA analysis and AUC scores. Second, we address the difficult problem of predicting DILI using available microarray data. Using a binary classification framework, our results suggest that rat in vivo data are more informative than human in vitro data to predict DILI.