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Functional and Structural Divergence Prediction of Proteins from Molecular Phylogenetic Analysis with Special Reference to Energy Metabolism System and Nervous System
https://ir.soken.ac.jp/records/998
https://ir.soken.ac.jp/records/9986d15bc55-b052-4e14-b860-3e68dde9225b
| 名前 / ファイル | ライセンス | アクション |
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要旨・審査要旨 / Abstract, Screening Result (398.5 kB)
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本文 (4.3 MB)
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| Item type | 学位論文 / Thesis or Dissertation(1) | |||||
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| 公開日 | 2010-02-22 | |||||
| タイトル | ||||||
| タイトル | Functional and Structural Divergence Prediction of Proteins from Molecular Phylogenetic Analysis with Special Reference to Energy Metabolism System and Nervous System | |||||
| タイトル | ||||||
| タイトル | Functional and Structural Divergence Prediction of Proteins from Molecular Phylogenetic Analysis with Special Reference to Energy Metabolism System and Nervous System | |||||
| 言語 | en | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_46ec | |||||
| 資源タイプ | thesis | |||||
| 著者名 |
富木, 毅
× 富木, 毅 |
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| フリガナ |
トミキ, タケシ
× トミキ, タケシ |
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| 著者 |
TOMIKI, Takeshi
× TOMIKI, Takeshi |
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| 学位授与機関 | ||||||
| 学位授与機関名 | 総合研究大学院大学 | |||||
| 学位名 | ||||||
| 学位名 | 博士（理学） | |||||
| 学位記番号 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | 総研大甲第769号 | |||||
| 研究科 | ||||||
| 値 | 生命科学研究科 | |||||
| 専攻 | ||||||
| 値 | 18 遺伝学専攻 | |||||
| 学位授与年月日 | ||||||
| 学位授与年月日 | 2004-03-24 | |||||
| 学位授与年度 | ||||||
| 値 | 2003 | |||||
| 要旨 | ||||||
| 内容記述タイプ | Other | |||||
| 内容記述 | Combinations of various functional systems are used in organisms for living, and each system is composed of various proteins. I predicted how functional systems had been evolved and how protein functions in each functional system had changed through molecular phylogenetic analyses.<br /> In this study, I tried to predict the evolution of functional systems by superimposition of phylogenetic trees constructed by as many homologous proteins in the functional systems as possible. Under the assumption that the divergences of proteins in functional systems correspond to the divergences of functional systems, I superimposed phylogenetic trees of proteins in functional systems, and inferred the deduced phylogenetic tree of the functional systems. I did phylogenetic analysis at system level to predict phylogeny of functional systems.<br /> Some of proteins are composed of multiple functional domains, and each domain might be inserted or deleted through evolution. Insertions or deletions of functional domains have changed protein functions. I tried to predict how domain compositions had changed through evolution and how protein functions had diversified by domain insertions and deletions through molecular phylogenetic analyses. I did phylogenetic analysis at the domain level by constructing composite gene trees so as to predict protein function changes in functional systems.<br /> It is possible that protein functions are different even if domain compositions of proteins are the same. I tried to predict the essential amino acid substitutions for changing protein functions through evolution referring to phylogenetic trees and amino acid sequences which cannot be detected by domain level analysis. I did phylogenetic analysis at the amino acid level to predict protein function changes in functional systems.<br /> As I described above, I predicted the evolution of functional systems and protein function changes in the functional systems at the three levels; system level, domain level and amino acid level. I applied the three level predictions to the two functional systems; electron transfer energy metabolism system (chapter 2) and neurotransmission system (chapter 3). The four electron transfer energy metabolism systems (photosynthesis, aerobic respiration, denitrification and sulfur respiration) share common characteristic features. Furthermore, homologous proteins exist among the four systems. They suggest that the four systems are evolutionarily related. But the exhaustive phylogenetic analysis of proteins among the four systems has not been tried yet. Therefore, I decided to try the three level predictions in the four energy metabolism systems to infer the phylogeny of the four systems and the protein function changes in the four systems. I constructed molecular phylogenetic trees by using amino acid sequences of functional domains. These trees and amino acid compositions of proteins suggest that domain insertions and deletions in the four systems made functions of electron transfer in proteins change. I tried to predict ligand binging specificities of catalytic proteins at the amino acid level, but experimental data about ligand binding functions are not enough for doing such predictions. Therefore, I did not predict protein function changes at amino acid level. Most of proteins in the four systems are not homologous each other. Only some important proteins for generating energy are homologous among the four systems. It means that most of proteins have evolved independently, and few of proteins are conserved among the four systems. I tried to superimpose phylogenetic trees of homologous proteins in the four energy metabolism systems to predict the phylogeny of the four energy metabolisms, and the phylogeny of aerobic respiration, denitrification and sulfur respiration was predicted.<br /> The three level predictions were also applied to chemical neurotransmission system. Neurotransmitters except for neuropeptides are produced by synthases in presynaptic cells, and the neurotransmitters are released to synapse. The neurotransmitters in the synapse are captured by receptors in postsynaptic cells, and the postsynaptic cells are activated. The neurotransmitters in the synapse are uptaken by transporters in the presynaptic cells or degradated in the synapse, and the chemical neurotransmission is inactivated. There are various kinds of neurotransmitters, and synthases, receptors and transporters for each neurotransmitter exist in chemical neurotransmission system. Therefore, each functional system for chemical neurotransmission can be defined as a system composed of synthases, receptors and transporlers for each neurotransmission. I tried to predict how the chemical neurotransmission systems have been diversified by means of superimposing the phylogenetic trees of synthases, receptors and transporters. The phylogenetic trees of some synthases and some receptors are possible to superimpose, and the phylogenetic trees of some receptors and some transporters are also possible to superimpose. These proteins might evolve together. But most of other proteins seem to have evolved independently from this study. Therefore the unit of evolution is not system in chemical neurotransmission systems. I also did phylogenetic analyses of receptors at the domain level and the amino acid level. I inferred domain composition changes which had changed protein functions from the domain level analyses. Some domain changes seem to be essential for generating some receptors. The essential amino acid substitutions for changing ligand specificities were also predicted from the amino acid level analysis.<br /> Based on the phylogenetic analyses of energy metabolism and chemical neurotransmission system, I did phylogenetic analysis of voltage-gated potassium channels at two levels; domain level and amino acid level (chapter 4). Voltage-gated ion channels are important for generating action potentials in postsynaptic neurons after chemical neurotransmission. I focused on inactivation, one of the major electrophysiological features of voltage-gated ion channels, and predicted how the diversification of the inactivation had occurred. There are two kinds of inactivation in voltage-gated potassium channels. One is N-type inactivation which is sudden inactivation immediately after activation, the other one is C-type inactivation which is slow inactivation. Reffering to phylogenetic trees and domain compositions of voltage-gated potassium channels, domain composition changes seem not to affect inactivation differences. Previous studies suggest that the specific chemical features of 20 N-terminal amino acids are important for generating N-type inactivation. Therefore, I investigated the specific chemical features of 20 N-terminal amino acid sequences in voltage-gated potassium channels. The specific chemical features of the 20 amino acids which induce N-type inactivation are found in the three subtypes out of the 21 subtypes. A small number of amino acid substitutions might produce the three N-type inactivation subtypes. The specific chemical features are not found in 20 N-terminal amino acids in the other five subclasses which can generate N-type inactivation. The amino acid substitutions which produce the five subtypes may different from those of the three subtypes which have the specific chemical features in the 20 N-terminal amino acids.<br /> I did phylogenetic analyses at system, domain and amino acid levels. From system level analysis, most of proteins in functional systems seem to be evolved independently. Although functions have been conserved in energy metabolism systems and chemical neurotransmission system, most of proteins in these systems have not been conserved. Domain composition changes seem to be slower than a small number of amino acid substitutions referring to phylogenetic analyses in this study. The combinations of the slower domain composition changes and the faster amino acid substitutions may have changed protein functions and these combinations might produce divergence of protein functions. But the combinations might happen independent of evolution of functional systems. Functional systems may have conserved their functions by the combinations and been diversified also by the combinations. | |||||
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| 値 | 有 | |||||
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| 内容記述タイプ | Other | |||||
| 内容記述 | application/pdf | |||||
