The role of SmpB protein in trans-translation

AbstractThe function of SmpB protein in the trans-translation system was evaluated using the well-defined cell-free translation system consisting of purified ribosome, alanyl-tRNA synthetase and elongation factors. The analysis showed that SmpB protein enhances alanine-accepting activity of tmRNA and that SmpB protein and tmRNA are sufficient to complete the trans-translation process in the presence of translational components. Moreover, SmpB is indispensable in the addition of tag-peptide onto ribosomes by tmRNA. In particular, the A-site binding of tmRNA is inhibited in the absence of SmpB

多価不飽和脂肪酸を２位に結合するホスファチジルコリンの炭素アナローグの合成

Carbon analogues of Phosphatidylcholines having linoleic or arachidonic acid at the 2-position were synthesized. The synthetic route involves conversion of the polyunsaturated fatty acid iodination. The derivatives were converted to diols by LiAIH4 reduction and submitted to lipase-catalyzed monostearoylation in isopropylether. The mono-ester was converted to phoshatidylcholines by the usual phosphodiester synthesis.自然界に広く存在するホスフォリパーゼA2はグリセロリン脂質の2位のエステル結合を選択的に切断する酵素であり,消化,アラキドン酸カスケードの起動,リン脂質過酸化物の代謝等,生理作用に広く関わっている。本研究ではホスフォリパーゼA2の基質ミメテイックとしてホスファチジルコリンの2位エステル結合が炭素-炭素結合に置き換わった化合物をアラキドン酸とステアリン酸を出発原料としてリパーゼ触媒によるアシル化反応及び有機化学反応によって合成した

Presenilin-2 Mutation Causes Early Amyloid Accumulation and Memory Impairment in a Transgenic Mouse Model of Alzheimer's Disease

In order to clarify the pathophysiological role of presenilin-2 (PS2) carrying the Volga German Kindred mutation (N141I) in a conventional mouse model of Alzheimer's disease (AD) expressing amyloid precursor protein (APP) with the Swedish mutation (Tg2576 line), we generated a double transgenic mouse (PS2Tg2576) by crossbreeding the PS2 mutant with Tg2576 mice. Here, we demonstrate that the PS2 mutation induced the early deposition of amyloid β-protein (Aβ) at 2-3 months of age and progressive accumulation at 4-5 months of age in the brains of the mutant mice. The PS2 mutation also accelerated learning and memory impairment associated with Aβ accumulation at 4-5 months of age in Tg2576 mice. These results suggest that the PS2 mutation causes early cerebral amyloid accumulation and memory dysfunction. PS2Tg2576 mice are a suitable mouse model for studying amyloid-lowering therapies

Enhancing Inverse Problem Solutions with Accurate Surrogate Simulators and Promising Candidates

Deep-learning inverse techniques have attracted significant attention in recent years. Among them, the neural adjoint (NA) method, which employs a neural network surrogate simulator, has demonstrated impressive performance in the design tasks of artificial electromagnetic materials (AEM). However, the impact of the surrogate simulators' accuracy on the solutions in the NA method remains uncertain. Furthermore, achieving sufficient optimization becomes challenging in this method when the surrogate simulator is large, and computational resources are limited. Additionally, the behavior under constraints has not been studied, despite its importance from the engineering perspective. In this study, we investigated the impact of surrogate simulators' accuracy on the solutions and discovered that the more accurate the surrogate simulator is, the better the solutions become. We then developed an extension of the NA method, named Neural Lagrangian (NeuLag) method, capable of efficiently optimizing a sufficient number of solution candidates. We then demonstrated that the NeuLag method can find optimal solutions even when handling sufficient candidates is difficult due to the use of a large and accurate surrogate simulator. The resimulation errors of the NeuLag method were approximately 1/50 compared to previous methods for three AEM tasks. Finally, we performed optimization under constraint using NA and NeuLag, and confirmed their potential in optimization with soft or hard constraints. We believe our method holds potential in areas that require large and accurate surrogate simulators.Comment: 20 pages, 8 figure

Reaction dynamics analysis of an E. coli protein translation system by computational modeling

A single enzymatic reaction can often be described by Michaelis-Menten kinetics, but once reactions are connected to one other, it becomes difficult to understand and capture a complete description of the reaction dynamics due to its high dimensionality. To elucidate the dynamic features of a biologically relevant large-scale reaction network, we constructed a computational model of minimal protein synthesis consisting of 241 components and 968 reactions that synthesize the Met-Gly-Gly (MGG) peptide based on an Escherichia coli-based reconstituted in vitro translation (IVT) system [1]. We performed a simulation using parameters collected primarily from the literature and found that the rate of MGG peptide synthesis becomes nearly constant in minutes, thus achieving a steady-state similar to experimental observations. In addition, concentration changes to 70% of the components, including intermediates, reached a plateau in a few minutes. However, the concentration change of each component exhibits several temporal plateaus, or a quasi-stationary state (QSS), before reaching the final plateau. To understand the complex dynamics, we focused on whether the components reached a QSS, mapped the arrangement of components in a QSS in the entire reaction network structure and investigated time-dependent changes. We found that components in a QSS form clusters that grow over time but not in a linear fashion and that this process involves the collapse and regrowth of clusters before the formation of a final large single cluster. These observations might commonly occur in other large-scale biological reaction networks. This developed analysis might be useful for understanding large-scale enzymatic reactions, thereby extracting the characteristics of the reaction network, including phase transitions. As the reconstituted IVT has been used for various applications inducing directed evolution of membrane proteins [2,3], the developed computational model might be useful in further enhancement of the yield of synthesized proteins using the reconstituted IVT. Please click Additional Files below to see the full abstract