Biology subjects

Nakayama, K. I.

Publications and source records attributed to Nakayama, K. I..

3 recordsLinked to original sources

bioRxiv2018

mitoNEET Regulates Mitochondrial Iron Homeostasis Interacting with Transferrin Receptor

Iron is an essential trace element for regulation of redox and mitochondrial function, and then mitochondrial iron content is tightly regulated in mammals. We focused on a novel protein localized at the outer mitochondrial membrane. Immunoelectron microscopy revealed transferrin receptor (TfR) displayed an intimate relationship with the mitochondria, and mass spectrometry analysis also revealed mitoNEET interacted with TfR in vitro. Moreover, mitoNEET was endogenously coprecipitated with TfR in the heart, which indicates that mitoNEET also interacts with TfR in vivo. We generated mice with cardiac-specific deletion of mitoNEET (mitoNEET-knockout). Iron contents in isolated mitochondria were significantly increased in mitoNEET-knockout mice compared to control mice. Mitochondrial reactive oxygen species (ROS) were higher, and mitochondrial maximal capacity and reserve capacity were significantly decreased in mitoNEET-knockout mice, which was consistent with cardiac dysfunction evaluated by echocardiography. The complex formation of mitoNEET with TfR may regulate mitochondrial iron contents via an influx of iron. A disruption of mitoNEET could thus be involved in mitochondrial ROS production by iron overload in the heart.

cell biology↗

bioRxiv2017

Trans-omic analysis reveals fed and fasting insulin signal across phosphoproteome, transcriptome, and metabolome

The concentration and temporal pattern of insulin selectively regulate multiple cellular functions. To understand how insulin dynamics are interpreted by cells, we constructed a trans-omic network of insulin action in FAO hepatoma cells from three networks--a phosphorylation-dependent cellular functions regulatory network using phosphoproteomic data, a transcriptional regulatory network using phosphoproteomic and transcriptomic data, and a metabolism regulatory network using phosphoproteomic and metabolomic data. With the trans-omic regulatory network, we identified selective regulatory networks that mediate differential responses to insulin. Akt and Erk, hub molecules of insulin signaling, encode information of a wide dynamic range of dose and time of insulin. Down-regulated genes and metabolites in glycolysis had high sensitivity to insulin (fasting insulin signal); up-regulated genes and dicarboxylic acids in the TCA cycle had low sensitivity (fed insulin signal). This integrated analysis enables molecular insight into how cells interpret physiologically fed and fasting insulin signals.\n\nHighlightsO_LIWe constructed a trans-omic network of insulin action using multi-omic data.\nC_LIO_LIThe trans-omic network integrates phosphorylation, transcription, and metabolism.\nC_LIO_LIWe classified signaling, transcriptome, and metabolome by sensitivity to insulin.\nC_LIO_LIWe identified fed and fasting insulin signal flow across the trans-omic network.\nC_LI

systems biology↗

bioRxiv2016

Lower brain pH as a shared endophenotype of psychotic disorders

Lower pH is a well-replicated finding in the postmortem brains of patients with schizophrenia and bipolar disorder. Interpretation of the data, however, is controversial as to whether this finding reflects a primary feature of the diseases or is a result of confounding factors such as medication, postmortem interval, and agonal state. To date, systematic investigation of brain pH has not been undertaken using animal models, which can be studied without confounds inherent in human studies. In the present study, we first confirmed that the brains of patients with schizophrenia and bipolar disorder exhibit lower pH values by conducting a meta-analysis of existing datasets. We then utilized neurodevelopmental mouse models of psychiatric disorders in order to test the hypothesis that lower brain pH exists in these brains compared to controls due to the underlying pathophysiology of the disorders. We measured pH, lactate levels, and related metabolite levels in brain homogenates from three mouse models of schizophrenia (Schnurri-2 KO, forebrain-specific calcineurin KO, and neurogranin KO mice) and one of bipolar disorder (Camk2a HKO mice), and one of autism spectrum disorders (Chd8 HKO mice). All mice were drug-naive with the same postmortem interval and agonal state at death. Upon postmortem examination, we observed significantly lower pH and higher lactate levels in the brains of model mice relative to controls. There was a significant negative correlation between pH and lactate levels. These results suggest that lower pH associated with increased lactate levels is a pathophysiology of such diseases rather than mere artifacts.

neuroscience↗