Biology subjects

Tanabe, K.

Publications and source records attributed to Tanabe, K..

3 recordsLinked to original sources

bioRxiv2018

The novel lncRNA lnc-NR2F1 is pro-neurogenic and mutated in human neurodevelopmental disorders

Long noncoding RNAs (lncRNAs) have been shown to act as important cell biological regulators including cell fate decisions but are often ignored in human genetics. Combining differential lncRNA expression during neuronal lineage induction with copy number variation morbidity maps of a cohort of children with autism spectrum disorder/intellectual disability versus healthy controls revealed focal genomic mutations affecting several lncRNA candidate loci. Here we find that a t(5:12) chromosomal translocation in a family manifesting neurodevelopmental symptoms disrupts specifically lnc-NR2F1. We further show that lnc-NR2F1 is an evolutionarily conserved lncRNA functionally enhances induced neuronal cell maturation and directly occupies and regulates transcription of neuronal genes including autism-associated genes. Thus, integrating human genetics and functional testing in neuronal lineage induction is a promising approach for discovering candidate lncRNAs involved in neurodevelopmental diseases.

neuroscience↗

bioRxiv2017

Image-based profiling can discriminate the effects of inhibitors on signaling pathways under differential ligand stimulation

A major advantage of image-based phenotypic profiling of compounds is that numerous image features can be sampled and quantitatively evaluated in an unbiased way. However, since this assay is a discovery-oriented screening, it is difficult to determine the optimal experimental set-up in advance. In this study, we examined whether variable cellular stimulation affects the efficacy of image-based profiling of compounds. Seven different EGF receptor ligands were used, and the expression of EGF receptor signaling molecules was monitored at various time points. Significant quantitative differences in image features were detected among the differentially treated samples. Next, 14 different compounds that affect EGF receptor signaling were profiled. Nearly half of the compounds were classified into distinct clusters, irrespective of differential ligand stimulation. The results suggest that image-based phenotypic profiling is quite robust in its ability to predict compound interaction with its target. Although this method will have to be validated in other experimental systems, the robustness of image-based compound profiling demonstrated in this work provides a valid basis for further study and its extended application.

pharmacology and toxicology↗

bioRxiv2017

High-Throughput Laboratory Evolution Of Escherichia coli Under Multiple Stress Environments

Bacterial cells have a remarkable capacity to adapt and to evolve to environmental changes. Although many mutations contributing to adaptive evolution have been identified, the relationship between the mutations and the phenotypic changes responsible for fitness gain has yet to be fully elucidated. For a better understanding of phenotype-genotype relationship in evolutionary dynamics, we performed high-throughput laboratory evolution of Escherichia coli under various stress conditions using an automated culture system. One measure of phenotype, transcriptome analysis, revealed that the expression changes which occurred during the evolution were generally similar among the strains evolved in the same stress environment. We also found several genes and gene functions for which mutations were commonly fixed in the strains resistant to the same stress, and whose effects on resistance were verified experimentally. We demonstrated that the integration of transcriptome and genome data enables us to extract the mechanisms for stress resistance.\n\nAuthor summaryUnderstanding the relationship between phenotypic and genetic changes is a fundamental goal in evolutionary biology, which can provide insights into the past and future evolutionary trajectories. Evolution of microorganisms in a laboratory has been the primary approach to clarify the mappings of phenotypic and genotypic changes. Here, we performed high-throughput laboratory evolution with bacteria using an automated culture system, to quantify phenotypic and genotypic changes occurred under various stress conditions. We identified various stress-specific gene expression changes and mutations, and contributions of them to fitness gain were validated. These results demonstrated that the integration of phenotypic and genotypic changes makes it possible to extract the mechanisms for stress resistance evolution, which will contribute to bioengineering applications.

evolutionary biology↗