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Search Results: 1 - 10 of 50685 matches for " Y. Takemoto "
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Fungicidal Activities and Mechanisms of Action of Pseudomonas syringae pv. syringae Lipodepsipeptide Syringopeptins 22A and 25A
Jon Y. Takemoto
Frontiers in Microbiology , 2011, DOI: 10.3389/fmicb.2011.00216
Abstract: The plant-associated bacterium Pseudomonas syringae pv. syringae simultaneously produces two classes of metabolites: the small cyclic lipodepsinonapeptides such as the syringomycins and the larger cyclic lipodepsipeptide syringopeptins SP22 or SP25. The syringomycins inhibit a broad spectrum of fungi (but particularly yeasts) by lipid-dependent membrane interaction. The syringopeptins are phytotoxic and inhibitory to Gram-positive bacteria. In this study, the fungicidal activities of two major syringopeptins, SP22A and SP25A, and their mechanisms of action were investigated and compared to those of syringomycin E. SP22A and SP25A were observed to inhibit the fungal yeasts Saccharomyces cerevisiae and Candida albicans although less effectively than syringomycin E. S. cerevisiae mutants defective in ergosterol and sphingolipid biosyntheses were less susceptible to SP22A and SP25A but the relative inhibitory capabilities of SRE vs. SP22A and SP25A were maintained. Similar differences were observed for capabilities to cause cellular K+ and Ca2+ fluxes in S. cerevisiae. Interestingly, in phospholipid bilayers the syringopeptins are found to induce larger macroscopic ionic conductances than syringomycin E but form single channels with similar properties. These findings suggest that the syringopeptins target the yeast plasma membrane, and, like syringomycin E, employ a lipid-dependent channel-forming mechanism of action. The differing degrees of growth inhibition by these lipodepsipeptides may be explained by differences in their hydrophobicities. The more hydrophobic SP22A and SP25A might interact more strongly with the yeast cell wall that would create a selective barrier for their incorporation into the plasma membrane.
Membrane Lipid-Modulated Mechanism of Action and Non-Cytotoxicity of Novel Fungicide Aminoglycoside FG08
Sanjib Shrestha, Michelle Grilley, Marina Y. Fosso, Cheng-Wei T. Chang, Jon Y. Takemoto
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0073843
Abstract: A novel aminoglycoside, FG08, that differs from kanamycin B only by a C8 alkyl chain at the 4″-O position, was previously reported. Unlike kanamycin B, FG08 shows broad-spectrum fungicidal but not anti-bacterial activities. To understand its specificity for fungi, the mechanism of action of FG08 was studied using intact cells of the yeast Saccharomyces cerevisiae and small unilamellar membrane vesicles. With exposure to FG08 (30 μg mL?1), 8-fold more cells were stained with fluorescein isothiocyanate, cells had 4 to 6-fold higher K+ efflux rates, and 18-fold more cells were stained with SYTOX Green in comparison to exposure to kanamycin B (30 μg mL?1). Yeast mutants with aberrant membrane sphingolipids (no sphingoid base C4 hydroxyl group, truncated very long fatty acid chain, or lacking the terminal phosphorylinositol group of mannosyl-diinositolphosphorylphytocerami?dewere 4 to 8-fold less susceptible to growth inhibition with FG08 and showed 2 to 10-fold lower SYTOX Green dye uptake rates than did the isogenic wild-type strain. FG08 caused leakage of pre-loaded calcein from 50% of small unilamellar vesicles with glycerophospholipid and sterol compositions that mimic the compositions of fungal plasma membranes. Less than 5 and 10% of vesicles with glycerophospholipid and sterol compositions that mimic bacterial and mammalian cell plasma membranes, respectively, showed calcein leakage. In tetrazolium dye cytotoxicity tests, mammalian cell lines NIH3T3 and C8161.9 showed FG08 toxicity at concentrations that were 10 to 20-fold higher than fungicidal minimal inhibitory concentrations. It is concluded that FG08’s growth inhibitory specificity for fungi lie in plasma membrane permeability changes involving mechanisms that are modulated by membrane lipid composition.
Amino Acids That Centrally Influence Blood Pressure and Regional Blood Flow in Conscious Rats
Yumi Takemoto
Journal of Amino Acids , 2012, DOI: 10.1155/2012/831759
Abstract: Functional roles of amino acids have increasingly become the focus of research. This paper summarizes amino acids that influence cardiovascular system via the brain of conscious rats. This paper firstly describes why amino acids are selected and outlines how the brain regulates blood pressure and regional blood flow. This section includes a concise history of amino acid neurotransmitters in cardiovascular research and summarizes brain areas where chemical stimulations produce blood pressure changes mainly in anesthetized animals. This is followed by comments about findings regarding several newly examined amino acids with intracisternal stimulation in conscious rats that produce changes in blood pressure. The same pressor or depressor response to central amino acid stimulations can be produced by distinct mechanisms at central and peripheral levels, which will be briefly explained. Thereafter, cardiovascular actions of some of amino acids at the mechanism level will be discussed based upon findings of pharmacological and regional blood flow measurements. Several examined amino acids in addition to the established neurotransmitter amino acids appear to differentially activate brain structures to produce changes in blood pressure and regional blood flows. They may have physiological roles in the healthy brain, but pathological roles in the brain with cerebral vascular diseases such as stroke where the blood-brain barrier is broken. 1. Introduction When the rat spontaneously performs an action such as grooming [1] or walking [2], changes in regional blood flows for head and legs are produced. The brain appropriately regulates blood supply to organs needed for planning of each behavior. For matching cardiovascular demand to each behavior, various kinds of potential neurotransmitters and neuromodulators should work in neuronal networks of the brain relating to the cardiovascular system and behavioral planning. A list of neurotransmitters includes the amino acids glutamate and GABA (gamma-amino-butyric acid) which are well established as endogenously produced excitatory and inhibitory agonists, respectively [3], and appear to play a pivotal role in the central nervous system relating to cardiovascular regulation [4–7]. However, it has been expanding to range the kind and the number of mediators between brain cells from classic neurotransmitter biogenic amines to gaseous neurotransmitters [8] and to gliotransmitters [9]. With respect to amino acids, the concentration of most amino acids in the cerebrospinal fluid is lower than those in the blood [10]. The
Intracisternally Injected L-Proline Activates Hypothalamic Supraoptic, but Not Paraventricular, Vasopressin-Expressing Neurons in Conscious Rats
Yumi Takemoto
Journal of Amino Acids , 2011, DOI: 10.4061/2011/230613
Abstract: When injected into specific rat brain regions, the neurotransmitter candidate L-proline produces various cardiovascular changes through ionotropic excitatory amino acid receptors. The present study used an immunohistochemical double-labeling approach to determine whether intracisternally injected L-proline in freely moving rats, which increases blood pressure, activates hypothalamic vasopressin-expressing neurons and ventral medullary tyrosine-hydroxylase- (TH-) containing neurons. Following injection of L-proline, the number of activated hypothalamic neurons that coexpressed vasopressin and c-Fos was much greater in the supraoptic nucleus (SON) than in the paraventricular nucleus (PVN) of rats with increased blood pressure. The number of activated TH-containing neurons was significantly greater following L-proline treatment than following control injections of artificial cerebrospinal fluid (ACSF). These results clearly demonstrate that intracisternally injected L-proline activates hypothalamic supraoptic, but not paraventricular, vasopressin-expressing neurons and medullary TH-containing (A1/C1) neurons in freely moving rats. 1. Introduction The nonessential imino acid L-proline has been proposed to be a neurotransmitter or neuromodulator of the central nervous system [1–3]. It produces various functional changes in animals, such as cardiovascular changes in rats [4–8] and sedation as well as hypnotic effects under stressful conditions in chicks [9, 10]. Intracisternal injections of L-proline, but not D-proline, have been shown to cause an increase in blood pressure in freely moving rats in a dose-dependent manner via ionotropic excitatory amino acid receptors in the brain [4, 5, 11]. This hypertensive response to centrally administered L-proline can be almost inhibited by intravenous preinjection of a vasopressin V1 receptor antagonist alone and augmented in ganglionic blocking rats where the augmented response was completely abolished by the additional vasopressin receptor antagonist [11], suggesting that the L-proline-induced pressor response could be mainly mediated by the release of hypothalamic vasopressin into the blood stream. Previous studies have shown that intracisternally injected dye robustly stains the medullary surface [12, 13]. These results suggest that intracisternally injected L-proline might diffuse and reach the medullary A1 catecholamine neurons, which send their terminals to vasopressin-expressing neurons in both the paraventricular nucleus (PVN) and the supraoptic nucleus (SON) of the hypothalamus [14]. The goal of this study
Current Understanding of the Formation and Adaptation of Metabolic Systems Based on Network Theory
Kazuhiro Takemoto
Metabolites , 2012, DOI: 10.3390/metabo2030429
Abstract: Formation and adaptation of metabolic networks has been a long-standing question in biology. With recent developments in biotechnology and bioinformatics, the understanding of metabolism is progressively becoming clearer from a network perspective. This review introduces the comprehensive metabolic world that has been revealed by a wide range of data analyses and theoretical studies; in particular, it illustrates the role of evolutionary events, such as gene duplication and horizontal gene transfer, and environmental factors, such as nutrient availability and growth conditions, in evolution of the metabolic network. Furthermore, the mathematical models for the formation and adaptation of metabolic networks have also been described, according to the current understanding from a perspective of metabolic networks. These recent findings are helpful in not only understanding the formation of metabolic networks and their adaptation, but also metabolic engineering.
Does Habitat Variability Really Promote Metabolic Network Modularity?
Kazuhiro Takemoto
PLOS ONE , 2013, DOI: 10.1371/journal.pone.0061348
Abstract: The hypothesis that variability in natural habitats promotes modular organization is widely accepted for cellular networks. However, results of some data analyses and theoretical studies have begun to cast doubt on the impact of habitat variability on modularity in metabolic networks. Therefore, we re-evaluated this hypothesis using statistical data analysis and current metabolic information. We were unable to conclude that an increase in modularity was the result of habitat variability. Although horizontal gene transfer was also considered because it may contribute for survival in a variety of environments, closely related to habitat variability, and is known to be positively correlated with network modularity, such a positive correlation was not concluded in the latest version of metabolic networks. Furthermore, we demonstrated that the previously observed increase in network modularity due to habitat variability and horizontal gene transfer was probably due to a lack of available data on metabolic reactions. Instead, we determined that modularity in metabolic networks is dependent on species growth conditions. These results may not entirely discount the impact of habitat variability and horizontal gene transfer. Rather, they highlight the need for a more suitable definition of habitat variability and a more careful examination of relationships of the network modularity with horizontal gene transfer, habitats, and environments.
Metabolic networks are almost nonfractal: A comprehensive evaluation
Kazuhiro Takemoto
Physics , 2014, DOI: 10.1103/PhysRevE.90.022802
Abstract: Network self-similarity or fractality are widely accepted as an important topological property of metabolic networks; however, recent studies cast doubt on the reality of self-similarity in the networks. Therefore, we perform a comprehensive evaluation of metabolic network fractality using a box-covering method with an earlier version and the latest version of metabolic networks, and demonstrate that the latest metabolic networks are almost self-dissimilar, while the earlier ones are fractal, as reported in a number of previous studies. This result may be because the networks were randomized because of an increase in network density due to database updates, suggesting that the previously observed network fractality was due to a lack of available data on metabolic reactions. This finding may not entirely discount the importance of self-similarity of metabolic networks. Rather, it highlights the need for a more suitable definition of network fractality and a more careful examination of self-similarity of metabolic networks.
Metabolic network modularity arising from simple growth processes
Kazuhiro Takemoto
Quantitative Biology , 2012, DOI: 10.1103/PhysRevE.86.036107
Abstract: Metabolic networks consist of linked functional components, or modules. The mechanism underlying metabolic network modularity is of great interest not only to researchers of basic science but also to those in fields of engineering. Previous studies have suggested a theoretical model, which proposes that a change in the evolutionary goal (system-specific purpose) increases network modularity, and this hypothesis was supported by statistical data analysis. Nevertheless, further investigation has uncovered additional possibilities that might explain the origin of network modularity. In this work, we propose an evolving network model without tuning parameters to describe metabolic networks. We demonstrate, quantitatively, that metabolic network modularity can arise from simple growth processes, independent of the change in the evolutionary goal. Our model is applicable to a wide range of organisms, and appears to suggest that metabolic network modularity can be more simply determined than previously thought. Nonetheless, our proposition does not serve to contradict the previous model; it strives to provide an insight from a different angle in the ongoing efforts to understand metabolic evolution, with the hope of eventually achieving the synthetic engineering of metabolic networks.
Habitat variability does not generally promote metabolic network modularity in flies and mammals
Kazuhiro Takemoto
Quantitative Biology , 2015,
Abstract: The evolution of species habitat range is an important topic over a wide range of research fields. In higher organisms, habitat range evolution is generally associated with genetic events such as gene duplication. However, the specific factors that determine habitat variability remain unclear at higher levels of biological organization (e.g., biochemical networks). One widely accepted hypothesis developed from both theoretical and empirical analyses is that habitat variability promotes network modularity; however, this relationship has not yet been directly tested in higher organisms. Therefore, I investigated the relationship between habitat variability and metabolic network modularity using compound and enzymatic networks in flies and mammals. Contrary to expectation, there was no clear positive correlation between habitat variability and network modularity. As an exception, the network modularity increased with habitat variability in the enzymatic networks of flies. However, the observed association was likely an artifact, and the frequency of gene duplication appears to be the main factor contributing to network modularity. These findings raise the question of whether or not there is a general mechanism for habitat range expansion at a higher level (i.e., above the gene scale). This study suggests that the currently widely accepted hypothesis for habitat variability should be reconsidered.
Heterogeneity of cells may explain allometric scaling of metabolic rate
Kazuhiro Takemoto
Quantitative Biology , 2015, DOI: 10.1016/j.biosystems.2015.02.003
Abstract: The origin of allometric scaling of metabolic rate is a long-standing question in biology. Several models have been proposed for explaining the origin; however, they have advantages and disadvantages. In particular, previous models only demonstrate either two important observations for the allometric scaling: the variability of scaling exponents and predominance of 3/4-power law. Thus, these models have a dispute over their validity. In this study, we propose a simple geometry model, and show that a hypothesis that total surface area of cells determines metabolic rate can reproduce these two observations by combining two concepts: the impact of cell sizes on metabolic rate and fractal-like (hierarchical) organization. The proposed model both theoretically and numerically demonstrates the approximately 3/4-power law although several different biological strategies are considered. The model validity is confirmed using empirical data. Furthermore, the model suggests the importance of heterogeneity of cell size for the emergence of the allometric scaling. The proposed model provides intuitive and unique insights into the origin of allometric scaling laws in biology, despite several limitations of the model.
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