Biology subjects

Watanabe, T.

Publications and source records attributed to Watanabe, T..

7 recordsLinked to original sources

bioRxiv2018

Causal evidence for LTP-based interference in visual learning

Training related skills in close succession results in interference but the reasons for this interference are not understood. Here we test the hypothesis that interference occurs due to competition of long-term potentiation (LTP): the LTP induced by one task impedes the LTP induced by the other. Human subjects performed two consecutive training sessions on different Gabor orientations. Immediately after the offset of the first training, we applied continuous theta burst stimulation (cTBS) to interfere with the LTP processes produced by the first training. We found that cTBS to a control site (vertex) resulted in substantial anterograde interference for the second training. Critically, cTBS to the visual cortex not only disrupted learning on the immediately preceding training, but also released the second training from the anterograde interference. These results provide strong support for the LTP-based theory of interference and suggest the possibility of directly manipulating the competition between different learning periods.

neuroscience↗

bioRxiv2018

Trained-feature specific offline learning in an orientation detection task

It has been suggested that sleep provides additional enhancement of visual perceptual learning (VPL) acquired before sleep, termed offline performance gains. A majority of the studies that found offline performance gains of VPL used discrimination tasks including the texture discrimination task (TDT). This makes it questionable whether offline performance gains on VPL are generalized to other visual tasks. The present study examined whether a Gabor orientation detection task, which is a standard task in VPL, shows offline performance gains. In Experiment 1, we investigated whether sleep leads to offline performance gains on the task. Subjects were trained with the Gabor orientation detection task, and re-tested it after a 12-hr interval that included either nightly sleep or only wakefulness. We found that performance on the task improved to a significantly greater degree after the interval that included sleep and wakefulness than the interval including wakefulness alone. In addition, offline performance gains were specific to the trained orientation. In Experiment 2, we tested whether offline performance gains occur by a nap. Also, we tested whether spontaneous sigma activity in early visual areas during non-rapid eye movement (NREM) sleep, previously implicated in offline performance gains of TDT, was associated with offline performance gains of the task. A different group of subjects had a nap with polysomnography. The subjects were trained with the task before the nap and re-tested after the nap. The performance of the task improved significantly after the nap only on the trained orientation. Sigma activity in the trained region of early visual areas during NREM sleep was significantly larger than in the untrained region, in correlation with offline performance gains. These aspects were also found with VPL of TDT. The results of the present study demonstrate that offline performance gains are not specific to a discrimination task such as TDT, and can be generalized to other forms of VPL tasks, along with trained-feature specificity. Moreover, the present results also suggest that sigma activity in the trained region of early visual areas plays an important role in offline performance gains of VPL of detection as well as discrimination tasks.

neuroscience↗

bioRxiv2018

A transgenic mutant mouse line accompanied by the complete deletion of interleukin-33 showed insulin and leptin resistances

Interleukin (IL) -33 has been identified as a member of the IL-1 family. Members of the IL-1 family have been reported to be involved in the regulation of energy homeostasis and glucose metabolism. Homozygous transgenic mutant mice of FLP14 line, that we previously generated, unexpectedly developed mature-onset obesity and diabetes. Through genetic investigations, we found that insertion of the transgenes had resulted in complete deletion of the Il33 gene. These obese male homozygous mutant mice exhibited hyperphagia with hyperleptinemia and insulin resistance caused by increased hepatic gluconeogenesis and decreased glucose uptake in skeletal muscle. As a result of examining preobese male homozygous mutant mice to investigate with the exclusion of the effect of obesity, hyperphagia with hyperleptinemina and insulin resistance caused by decreased glucose uptake in skeletal muscle were already observed, but the increased hepatic glucose production was not. To investigate whether the insulin resistance was caused by deletion of the Il33 gene, we treated these preobese homozygous mutant mice with recombinant IL-33 protein and noted a significant improvement in insulin resistance. Thus, insulin resistance in these homozygous mutant mice was caused, at least in part, by IL-33 deficiency, suggesting a favorable role of IL-33 for glucose metabolism in the skeletal muscle.

molecular biology↗

bioRxiv2018

Network-guided Discovery of Influenza Virus Replication Host Factors

The position of host factors required for viral replication within a human protein-protein interaction (PPI) network can be exploited to identify drug targets that are robust to drug-mediated selective pressure. Host factors can physically interact with viral proteins, be a component of pathways regulated by viruses (where proteins themselves do not interact with viral proteins) or be required for viral replication but unregulated by viruses. Here, we demonstrate a method of combining a human PPI network with virus-host protein interaction data to improve antiviral drug discovery for influenza viruses by identifying target host proteins. Network analysis shows that influenza virus proteins physically interact with host proteins in network positions significant for information flow. We have isolated a subnetwork of the human PPI network which connects virus-interacting host proteins to host factors that are important for influenza virus replication without physically interacting with viral proteins. The subnetwork is enriched for signaling and immune processes. Selecting proteins based on network topology within the subnetwork, we performed an siRNA screen to determine if the subnetwork was enriched for virus replication host factors and if network position within the subnetwork offers an advantage in prioritization of drug targets to control influenza virus replication. We found that the subnetwork is highly enriched for target host proteins - more so than the set of host factors that physically interact with viral proteins. Our findings demonstrate that network positions are a powerful predictor to guide antiviral drug candidate prioritization.\n\nIMPORTANCEIntegrating virus-host interactions with host protein-protein interactions, we have created a method using these established network practices to identify host factors (i.e. proteins) that are likely candidates for antiviral drug targeting. We demonstrate that interaction cascades between host proteins that directly interact with viral proteins and host factors that are important to influenza replication are enriched for signaling and immune processes. Additionally, we show that host proteins that interact with viral proteins are in network locations of power. Finally, we demonstrate a new network methodology to predict novel host factors and validate predictions with an siRNA screen. Our results show that integrating virus-host proteins interactions is useful in the identification of antiviral drug target candidates.

systems biology↗

bioRxiv2018

Comparison of the 3-D patterns of the parasympathetic nervous system in the lung at late developmental stages between mouse and chicken

Although the basic schema of the body plan is similar among different species of amniotes (mammals, birds, and reptiles), the lung is an exception. Here, anatomy and physiology are considerably different, particularly between mammals and birds. In mammals, inhaled and exhaled airs mix in the airways, whereas in birds the inspired air flows unidirectionally without mixing with the expired air. This bird-specific respiration system is enabled by the complex tubular structures called parabronchi where gas exchange takes place, and also by the bellow-like air sacs appended to the main part of the lung. That the lung is predominantly governed by the parasympathetic nervous system has been shown mostly by physiological studies in mammals. However, how the parasympathetic nervous system in the lung is established during late development has largely been unexplored both in mammals and birds. In this study, by combining immunocytochemistry, the tissue-clearing CUBIC method, and ink-injection to airways, we have visualized the 3-D distribution patterns of parasympathetic nerves and ganglia in the lung at late developmental stages of mice and chickens. These patterns were further compared between these species, and three prominent similarities emerged: (1) parasympathetic postganglionic fibers and ganglia are widely distributed in the lung covering the proximal and distal portions, (2) the gas exchange units, alveoli in mice and parabronchi in chickens, are devoid of parasympathetic nerves, (3) parasympathetic nerves are in close association with smooth muscle cells, particularly at the base of the gas exchange units. These observations suggest that despite gross differences in anatomy, the basic mechanisms underlying parasympathetic control of smooth muscles and gas exchange might be conserved between mammals and birds.\n\nHighlightsO_LI3-D patterns of parasympathetic nerves are visualized in mouse and chicken lungs.\nC_LI\n\nComparison of these patterns reveals three prominent similarities between mouse and chicken: O_LIVAChT-positive postganglionic fibers and ganglia are widely distributed in the lung.\nC_LIO_LIGas exchange units are devoid of parasympathetic nerves.\nC_LIO_LIParasympathetic nerves are in close association with smooth muscle cells.\nC_LI

developmental biology↗

bioRxiv2017

Feature-specific awake reactivation in human V1 after visual training

Converging human studies have demonstrated that brain activity patterns observed during task performance reemerge in the following restful awake state. Such \"awake reactivation\" has been demonstrated across higher-order cortex for complex images or associations. However, it remains unclear what specific training components are reactivated in these studies. Here we sought to provide evidence for the reactivation of a particular visual feature - Gabor orientation. Following extensive training on a visual task, we found robust reactivation in human V1 that lasted at least eight minutes. This effect was not present in higher retinotopic areas such as V2, V3, V3A, or V4v, demonstrating that the effects in V1 are not due to top-down processes such as conscious rehearsal. Furthermore, the amount of awake reactivation predicted the amount of performance improvement on the visual task. These results demonstrate that functionally-relevant awake reactivation of specific visual features occurs in early sensory cortex.

neuroscience↗

bioRxiv2017

Harmonization Of Multi-Site Diffusion Tensor Imaging Data

Diffusion tensor imaging (DTI) is a well-established magnetic resonance imaging (MRI) technique used for studying microstructural changes in the white matter. As with many other imaging modalities, DTI images suffer from technical between-scanner variation that hinders comparisons of images across imaging sites, scanners and over time. Using fractional anisotropy (FA) and mean diffusivity (MD) maps of 205 healthy participants acquired on two different scanners, we show that the DTI measurements are highly site-specific, highlighting the need of correcting for site effects before performing downstream statistical analyses. We first show evidence that combining DTI data from multiple sites, without harmonization, is counter-productive and negatively impacts the inference. Then, we propose and compare several harmonization approaches for DTI data, and show that ComBat, a popular batch-effect correction tool used in genomics, performs best at modeling and removing the unwanted inter-site variability in FA and MD maps. Using age as a biological phenotype of interest, we show that ComBat both preserves biological variability and removes the unwanted variation introduced by site. Finally, we assess the different harmonization methods in the presence of different levels of confounding between site and age, in addition to test robustness to small sample size studies.

neuroscience↗