Biology subjects

Tamura, T.

Publications and source records attributed to Tamura, T..

44 records · Page 3Linked to original sources

bioRxiv2021

Macrophages govern antiviral responses in human lung tissues protected from SARS-CoV-2 infection

The majority of SARS-CoV-2 infections among healthy individuals result in asymptomatic to mild disease. However, the immunological mechanisms defining effective lung tissue protection from SARS-CoV-2 infection remain elusive. Unlike mice solely engrafted with human fetal lung xenograft (fLX), mice co-engrafted with fLX and a myeloid-enhanced human immune system (HNFL mice) are protected against SARS-CoV-2 infection, severe inflammation, and histopathology. Effective control of viral infection in HNFL mice associated with significant macrophage infiltration, and the induction of a potent macrophage-mediated interferon response. The pronounced upregulation of the USP18-ISG15 axis (a negative regulator of IFN responses), by macrophages was unique to HNFL mice and represented a prominent correlate of reduced inflammation and histopathology. Altogether, our work shed light on unique cellular and molecular correlates of lung tissue protection during SARS-CoV-2 infection, and underscores macrophage IFN responses as prime targets for developing immunotherapies against coronavirus respiratory diseases. HIGHLIGHTSO_LIMice engrafted with human fetal lung xenografts (fLX-mice) are highly susceptible to SARS-CoV-2. C_LIO_LICo-engraftment with a human myeloid-enriched immune system protected fLX-mice against infection. C_LIO_LITissue protection was defined by a potent and well-balanced antiviral response mediated by infiltrating macrophages. C_LIO_LIProtective IFN response was dominated by the upregulation of the USP18-ISG15 axis. C_LI

microbiology↗

bioRxiv2020

SARS-CoV-2 Requires Cholesterol for Viral Entry and Pathological Syncytia Formation

Many enveloped viruses induce multinucleated cells (syncytia), reflective of membrane fusion events caused by the same machinery that underlies viral entry. These syncytia are thought to facilitate replication and evasion of the host immune response. Here, we report that co-culture of human cells expressing the receptor ACE2 with cells expressing SARS-CoV-2 spike, results in synapse-like intercellular contacts that initiate cell-cell fusion, producing syncytia resembling those we identify in lungs of COVID-19 patients. To assess the mechanism of spike/ACE2-driven membrane fusion, we developed a microscopy-based, cell-cell fusion assay to screen [~]6000 drugs and >30 spike variants. Together with cell biological and biophysical approaches, the screen reveals an essential role for membrane cholesterol in spike-mediated fusion, which extends to replication-competent SARS-CoV-2 isolates. Our findings provide a molecular basis for positive outcomes reported in COVID-19 patients taking statins, and suggest new strategies for therapeutics targeting the membrane of SARS-CoV-2 and other fusogenic viruses. HighlightsO_LICell-cell fusion at ACE2-spike clusters cause pathological syncytia in COVID-19 C_LIO_LIDrug screen reveals critical role for membrane lipid composition in fusion C_LIO_LISpikes unusual membrane-proximal cysteines and aromatics are essential for fusion C_LIO_LICholesterol tunes relative infectivity of SARS-CoV-2 viral particles C_LI

cell biology↗

bioRxiv2020

Microtubule Defect Involved in 'Mitophagy Resistance' Under Subacute Oxidative Stress - Potential Mechanism for Cellular Inflammation

IntroductionOxidative stress is considered an essential mechanism in ICU-acquired weakness. The roles of oxidative stress in autophagy/mitophagy dysfunction remains elusive. Microtubule serves as an essential guide rail for auto/mitophagosome trafficking required for proper maturation of auto/mitophagosomes in normal circumstances, and microtubules network formation is regulated by signal transduction mechanisms involving Akt, GSK3{beta}, and the microtubule plus-end tracking molecule, EB1. We have investigated (1) whether oxidative stress affects this pathway, leading to the defective mitophagy response, and (2) whether trehalose, an auto/mitophagy modulator, can ameliorate these pathological conditions. MethodsBy stably transfecting markers for auto/mitophagy or MT synthesis, we have established a few new C2C12 myocyte cell lines, expressing, GFP-LC3, EB1-GFP, and/or tandem-fluorescence LC3 (tfLC3). To monitor microtubule network, the cells were stained by SiR-tubulin. The cells were cultured in the presence or absence of oxidative stress by hydrogen peroxide (H2O2) and treated with or without trehalose. The response of mitophagy parameters including vesicle motion and the maturation status was monitored by stimulating the cells with carbonyl cyanide m-chlorophenyl hydrazone (CCCP), an established mitophagy inducer, under a time-lapse confocal microscopy. Signal transduction mechanisms linking mitophagy to microtubule formation was analyzed by Western Blotting against Akt and GSK3{beta}. ResultsCells under the oxidative stress, showed abolished MT network formation, decreased microtubule synthesis by EB1, and a decrease in CCCP-invoked response of mitophagosome motion, perturbed mitophagosome maturation, and increased superoxide production. Signal resistance of Akt/GSK3{beta} pathway to mitophagic stimulation, was documented. Trehalose treatment reversed signal resistance, diminished MT synthesis, ameliorated the disturbed MT network, and improved maturation defects, suppressing the production of superoxide. ConclusionsOxidative stress decreases the response of mitophagy and abolishes microtubule network. Trehalose improves the synthetic ability of microtubule and normalized the disturbed microtubule network, resulting in the improvement of the perturbed mitophagosomes maturation under the oxidative stress.

cell biology↗

bioRxiv2019

Comparative population genetic structure of two Ixodidae ticks (Ixodes ovatus and Haemaphysalis flava) in Niigata Prefecture, Japan

Ixodid tick species such as Ixodes ovatus and Haemaphysalis flava are essential vectors of tick-borne diseases in Japan. In this study, we investigated the population genetic structures and gene flow of I. ovatus and H. flava as affected by the tick host mobility. We hypothesized that I. ovatus and H. flava may have differences in their genetic structure due to the low mobility of small rodent hosts of I. ovatus at the immature stage in contrast to the mediated dispersal of avian hosts for immature H. flava. We collected 307 adult I. ovatus and 220 adult H. flava from 29 and 17 locations across Niigata Prefecture, Japan. We investigated the genetic structure at two mitochondrial loci (cox1, 16S rRNA gene). For I. ovatus, pairwise FST and analysis of molecular variance (AMOVA) analyses of cox1 sequences indicated significant genetic variation among populations. Both cox1 and 16S rRNA markers showed non-significant genetic variation among locations for H. flava. The Bayesian tree and haplotype network of cox1 marker for I. ovatus samples in Niigata Prefecture found 3 genetic groups wherein most haplotypes in group 2 were distributed in low altitudinal areas. When we added cox1 sequences of I. ovatus from China to the phylogenetic analysis, three genetic groups (China 1, China 2, and Niigata and Hokkaido, Japan) were formed in the tree suggesting the potential for cryptic species in the genetic group in Japan. Our results support our hypothesis and suggest that the host preference of ticks at the immature stage may influence the genetic structure and gene flow of the ticks. This information is vital in understanding the tick-host interactions in the field to better understand the tick-borne disease transmission and in designing an effective tick control program.

genetics↗

bioRxiv2019

The feasibility of atrial and ventricular arrhythmias recognition using metrics of signal complexity for heartbeat intervals

It is well known that the cardiac system is controlled by the complex nonlinear self-regulation and the heartbeat variability (HRV) is an independent indicator of the autonomic regulation. With the assumption that intrinsic differences of atrial fibrillation (A) and ventricular ectopic arrhythmias (V) can be unveiled by a proper approach based on of signal complexity, we examine the feasibility of detecting these arrhythmias of different pathological origins using metrics of complexity for heartbeat intervals (HRI). Specifically, the normal sinus rhythm (N), the A type and the V type are used as the targeted types of heartbeat. By extracting the entropy-based features from HRI of different lengths, i.e., from 300 heartbeats to 1000 heartbeats, we examined the distinguishability of these 3 types of heartbeat. By applying the features to the random forest model, the HRI signal of 600-heartbeat-length can be used to detect the A and V completely, i.e., with 100% of type-wise recall and precision. What is more, this approach is sensitive to the existence of the corresponding arrhythmias. The results substantiate our assumption about the intrinsic difference of the A and V type. A further investigation applying this approach to a wider spectrum and a finer stratification of arrhythmias/ cardiac diseases and may lead to the systematic understanding in the context of complexity and better insight for its practical use for wearable/unconstrained monitors.

physiology↗

bioRxiv2019

Growth-coupled overproduction is theoretically possiblefor most metabolites even in Saccharomyces cerevisiae under anaerobic condition

BackgroundMetabolic network analysis through flux balance is an established method for the computational redesign of production strains in metabolic engineering. The computational redesign is often based on reaction deletions from the original wild type networks. A key principle often used in this method is the production of target metabolites as by-products of cell growth. From a viewpoint of bioinformatics, it is very important to prepare a set of algorithms that can determine reaction deletions that achieve growth coupling whatever network topologies, target metabolites and parameter values will be considered in the future. Recently, the strong coupling-based method was used to demonstrate that the coupling of growth and production is possible for nearly all metabolites through reaction deletions in genome-scale metabolic models of Escherichia coli and Saccharomyces cerevisiae under aerobic conditions. However, when growing S. cerevisiae under anaerobic conditions, deletion strategies using the strong coupling-based method were possible for only 3.9% of all metabolites. Therefore, it is necessary to develop algorithms that can achieve growth coupling by reaction deletions for the conditions that the strong coupling-based method was not efficient. ResultsWe developed an algorithm that could calculate the reaction deletions that achieve the coupling of growth and production for 91.3% metabolites in genome-scale models of S. cerevisiae under anaerobic conditions. This analysis was conducted for the worst-case-scenario using flux variability analysis. To demonstrate the feasibility of the coupling, we derived appropriate reaction deletions using the new algorithm for target production in which the search space was divided into small cubes (CubeProd). ConclusionsWe developed a novel algorithm, CubeProd, to demonstrate that growth coupling is possible for most metabolites in S.cerevisiae under anaerobic conditions. This may imply that growth coupling is possible by reaction deletions for most target metabolites in any genome-scale constraint-based metabolic networks. The developed software, CubeProd, implemented in MATLAB, and the obtained reaction deletion strategies are freely available.

bioinformatics↗

bioRxiv2018

Limited uptake of essential amino acid is effective for cancer therapy in metabolic networks of integrated constraint-based models

Nam models are context-specific genome-scale metabolic models for nine types of cancer and corresponding normal cells reconstructed from RECON 2, genetic mutation information, and expression profile data. In this study, computational experiments were conducted using Nam models to find effective ratios of uptake reactions such that cancer cells do not grow while normal cells grow. The original Nam models were extended to consider interactions between cancer and normal cells using an approach developed for representing host-microbe interactions. When uptake ratio of only single reaction was allowed to change at a time, the results of computational experiments showed that every essential amino acid had effective ranges for almost all nine types of cancer, while the other uptake reactions rarely had such effective ranges.

bioinformatics↗

bioRxiv2017

Grid-based computational methods for the design of constraint-based parsimonious chemical reaction networks to simulate metabolite production: GridProd

Constraint-based metabolic flux analysis of knockout strategies is an efficient method to simulate the production of useful metabolites in microbes. Owing to the recent development of technologies for artificial DNA synthesis, it may become important in the near future to mathematically design minimum metabolic networks to simulate metabolite production. Accordingly, we have developed a computational method where parsimonious metabolic flux distribution is computed for designated constraints on growth and production rates which are represented by grids. When the growth rate of this obtained parsimonious metabolic network is maximized, higher production rates compared to those noted using existing methods are observed for many target metabolites. The set of reactions used in this parsimonious flux distribution consists of reactions included in the original genome scale model iAF1260. The computational experiments show that the grid size affects the obtained production rates. Under the conditions that the growth rate is maximized and the minimum cases of flux variability analysis are considered, the developed method produced more than 90% of metabolites, while the existing methods produced less than 50%. Mathematical explanations using examples are provided to demonstrate potential reasons for the ability of the proposed algorithm to identify design strategies that the existing methods could not identify. The source code is freely available, and is implemented in MATLAB and COBRA toolbox.\n\nAuthor summaryMetabolic networks represent the relationships between biochemical reactions and compounds in living cells. By computationally modifying a given metabolic network of microbes, we can simulate the effect of knockouts and estimate the production of valuable metabolites. A common mathematical model of metabolic networks is the constraint-based flux model. In constraint-based flux balance analysis, a pseudo-steady state is assumed to predict the metabolic profile where the sum of all incoming fluxes is equal to the sum of all outgoing fluxes for each internal metabolite. Based on these constraints, the biomass objective function, written as a linear combination of fluxes, is maximized. In this study, we developed an efficient method for computing the design of minimum metabolic networks by using constraint-based flux balance analysis to simulate the production of useful metabolites.

bioinformatics↗