Ataxin-3 Regulates Aggresome Formation of Copper-Zinc Superoxide Dismutase (SOD1) by Editing K63-linked Polyubiquitin Chains

Polyubiquitination of misfolded proteins, especially K63-linked polyubiquitination, is thought to be associated with the formation of inclusion bodies. However, it is not well explored whether appropriate editing of the different types of ubiquitin linkages by deubiquitinating enzymes (DUBs) affects the dynamics of inclusion bodies. In this study, we report that a specific DUB, ataxin-3, is required for the efficient recruitment of the neurodegenerative disease-associated protein copper-zinc superoxide dismutase (SOD1) to aggresomes. The overexpression of ataxin-3 promotes mutant SOD1 aggresome formation by trimming K63-linked polyubiquitin chains. Moreover, knockdown of ataxin-3 decreases mutant SOD1 aggresome formation and increases cell death induced by mutant SOD1. Thus, our data suggest that the sequestration of misfolded SOD1 into aggresomes, which is driven by ataxin-3, plays an important role in attenuating protein misfolding-induced cell toxicity.     

微生物燃料电池在毒性物质检测中的应用

微生物燃料电池(Microbial fuel cell,MFC)利用微生物整体作为催化剂催化底物将化学能直接转化为电能,是一种极具应用前景的生物电化学技术。微生物在阳极氧化还原有机物产生电子并传递给阳极,电子通过外电路传递至阴极后将电子释放给阴极中的氧化剂,从而产生电流。当有毒物质进入MFC,微生物活性降低,电子传递量变少,电流降低,而电流的产生与微生物活性呈线性关系,据此可检测样品的毒性。本文主要介绍了微生物燃料电池在毒性物质抗生素、重金属离子、有机污染物、酸等方面的研究,并分析了微生物燃料电池存在的问题及未来研究方向,以期不久的将来微生物燃料电池能付之使用。     

药用植物栀子的组织培养

栀子(Gardenia jasminoides)为药用木本植物。以栀子果皮、种子团和种子为外植体,研究不同激素配比及不同培养方式对愈伤组织诱导和芽分化的影响。研究结果表明,培养基成分为MS+0.5 mg·L–12,4-D+0.25 mg·L–16-BA较适宜果皮和种子愈伤组织的诱导,诱导率分别为83.3%和88.5%;培养基成分为MS+1.0 mg·L–12,4-D+1.0 mg·L–16-BA较适宜种子团愈伤组织的诱导,诱导率为78.1%。3种外植体诱导的愈伤组织中,只有种子愈伤组织能通过液体培养分化出芽;TDZ对芽分化有明显的促进作用;最佳的芽分化培养基为MS+0.05 mg·L–1NAA+0.10 mg·L–1TDZ,其愈伤组织分化率为8.75%。该研究以栀子种子为外植体,并获得了再生植株,为药用植物栀子转基因体系的建立奠定了基础。     

菌紫质的Ser和Lys残基修饰对BR结构和功能的影响

用化学修饰研究了菌紫质（ＢＲ）的结构和功能的变化。用氮氧自由基分别对赖氨酸和丝氨酸进行修饰,研究结果表明在圆二色谱上（ＣＤ谱）,与天然紫膜样品比较,两种自由基分别修饰赖氨酸（Ｌｙｓ）和丝氨酸（Ｓｅｒ）残基２４小时后的ＣＤ谱中均只有负峰,分别在５９６ｎｍ和６０２ｎｍ,５３５ｎｍ的正峰已消失,７２小时后５３５ｎｍ的正峰部分地恢复,但１２０小时后均未见进一步恢复。与未修饰的紫膜相比,两种自由基修饰的紫膜在Ｒａｍａｎ光谱上观察到中间体Ｍ４１２的相对量要明显增加。本文对这二种化学修饰引起的ＢＲ结构和功能变化进行了初步讨论。     

Differentiating the 2,3-diols of glucopyranosides by 4,6-O-benzylidene-protected-1,2-d-glucopyranosylorthoesters strategy

A facile and efficient method to differentiate the 2,3-diols of glucopyranosides based on 1,2-orthoesters strategy was developed. Stable thioglucosides were employed as the starting materials to prepare the corresponding 1,2-orthoesters. When treated with HCl aqueous solution and followed with Et₃N, differentiation of the 2,3-diols was efficiently achieved along with the generation of a convertible anomeric hydroxyl group. In addition, an easy and practical method based on NOE was proposed to determine whether the 1,2-orthoesters were endo-type or exo-type.     

Predicting protein fold types by the general form of Chou's pseudo amino acid composition: approached from optimal feature extractions

Identification on protein folding types is always based on the 27-class folds dataset, which was provided by Ding & Dubchak in 2001. But with the avalanche of protein sequences, fold data is also expanding, so it will be the inevitable trend to improve the existing dataset and expand more folding types. In this paper, we construct a multi-class protein fold dataset, which contains 3,457 protein chains with sequence identity below 35% and could be classified into 76 fold types. It was 4 times larger than Ding & Dubchak's dataset. Furthermore, our work proposes a novel approach of support vector machine based on optimal features. By combining motif frequency, low-frequency power spectral density, amino acid composition, the predicted secondary structure and the values of auto-correlation function as feature parameters set, the method adopts criterion of the maximum correlation and the minimum redundancy to filter these features and obtain a 95-dimensions optimal feature subset. Based on the ensemble classification strategy, with 95-dimensions optimal feature as input parameters of support vector machine, we identify the 76-class protein folds and overall accuracy measures up to 44.92% by independent test. In addition, this method has been further used to identify upgraded 27-class protein folds, overall accuracy achieves 66.56%. At last, we also test our method on Ding & Dubchak's 27-class folds dataset and obtained better identification results than most of the previous reported results.