The activation of amino acid analogues by phenylalanyl- and tyrosyl-tRNA synthetases from plants

Partially purified preparations of Phe- and Tyr-tRNA synthetases were obtained from seed or seedlings of Phaseolus aureus, Delonix regia and Caesalpinia tinctoria, and the ability of a variety of structural analogues of Phe or Tyr to act as alternative substrates or inhibitors was tested. 3-Hydroxymethylphenylalanine, a natural product of C. tinctoria, formed a particularly effective substrate for the Tyr-tRNA synthetase from P. aureus. The structural features commensurate with substrate activity in an analogue molecule are discussed.     

Determination of the pH dependence,substrate specificity,and turnovers of alternative substrates for human ornithine aminotransferase

Hepatocellular carcinoma (HCC) is the most common primary cancer of the liver and occurs predominantly in patients with underlying chronic liver diseases. Over the past decade, human ornithine aminotransferase (hOAT), which is an enzyme that catalyzes the metabolic conversion of ornithine into an intermediate for proline or glutamate synthesis, has been found to be overexpressed in HCC cells. hOAT has since emerged as a promising target for novel anticancer therapies, especially for the ongoing rational design effort to discover mechanism-based inactivators (MBIs). Despite the significance of hOAT in human metabolism and its clinical potential as a drug target against HCC, there are significant knowledge deficits with regard to its catalytic mechanism and structural characteristics. Ongoing MBI design efforts require in-depth knowledge of the enzyme active site, in particular, pKa values of potential nucleophiles and residues necessary for the molecular recognition of ligands. Here, we conducted a study detailing the fundamental active-site properties of hOAT using stopped-flow spectrophotometry and X-ray crystallography. Our results quantitatively revealed the pH dependence of the multistep reaction mechanism and illuminated the roles of ornithine α-amino and δ-amino groups in substrate recognition and in facilitating catalytic turnover. These findings provided insights of the catalytic mechanism that could benefit the rational design of MBIs against hOAT. In addition, substrate recognition and turnover of several fragment-sized alternative substrates of hOATs, which could serve as structural templates for MBI design, were also elucidated.     

典型河床底质组成中底栖动物群落及多样性

底栖动物是河流生态系统中食物链的重要环节。通过对长江、黄河、东江和拒马河等河流野外调查和采样分析研究了河床底质组成对底栖动物群落结构的影响规律。研究结果发现,不同河床底质组成中的底栖动物结构差别很大,不同地理位置而相同底质条件和水力条件的河流底栖动物群落组成相似,说明河床底质是影响河流底栖动物群落结构的关键因素,受地理位置和大气候的影响不大;利用多项生物指标分析了不同河床底质组成中底栖动物群落的多样性,卵石河床且有水生植物生长的河流底栖动物物种组成最丰富,大河中沙质河床不稳定,未采集到底栖动物;不同底质类型河床中的优势种群亦不同。并分析了采样所得底栖动物物种数与采样面积之间的关系,符合前者随后者呈幂指数增加的规律,当实测采样面积为1～2m^2时物种数变化不大,建议一般情况下最小采样面积应为1m^2。     

威廉环毛蚯蚓对土壤微生物量及活性的影响

探讨威廉环毛蚯蚓（Ｐｈｅｒｅｔｉｍａ ｇｕｉｌｌｅｌｍｉ）对土壤总微生物量,活性微生物量的影响,蚯蚓处理中（土壤与蚯蚓的比例为５：１,干重：活体重,处理时间为２４ｈ）,用熏蒸提取法测定的土壤总微生物量下降,用底物诱导呼吸法测定的活性微生物量和真菌与细菌比例无显著变化;蚯蚓处理土壤促进了被微生物固持的养分的释放和土壤微生物群体年轻化,增强了微生物的代谢商和纤维素分解活性,结合对文献资料的分析,讨论了     

森林生态系统土壤CO2释放随海拔梯度的变化及其影响因子

联合国气候框架公约的签署提升了人们对全球变暖、碳循环的关注。土壤CO₂释放作为土壤-大气CO₂交换的主要途径之一,成为了各国生态学家研究的重点内容。通过对1800~2155m海拔梯度上森林生态系统土壤CO₂释放进行研究,揭示了较小空间尺度上土壤CO₂释放的变化规律及其控制机制。在研究区域内,随着海拔梯度的增加,森林土壤CO₂释放由(1.94±006) μmol m^-2 s^-1逐渐增加至(2.22±0.07) μ mol m^-2 s^-1。土壤温度、土壤水分、土壤有机碳（SOC）、全N、全P与土壤CO₂释放呈显著正相关（n=14, P<0.05）;土壤容重与土壤CO₂释放速率呈显著负相关（n=14,P<0.05）;土壤pH对土壤CO₂释放影响不显著。作为一个复杂的生态学过程,环境因子及其交互作用对土壤CO₂释放产生影响,为了减少因子共线性影响,逐步降低因子维数,采用主成分分析（PCA）揭示了土壤温度、土壤水分、SOC、全N、全P、容重6个因子的联合作用,其累积贡献率达到了57％以上;进一步运用逐步回归分析方法,探讨了影响土壤CO₂释放沿海拔梯度分布的主导因子,结果表明土壤水分是研究区域森林生态系统土壤CO₂释放沿海拔梯度变化的主导因子。     

Structural basis of substrate specificity in the serine proteases.

Structure-based mutational analysis of serine protease specificity has produced a large database of information useful in addressing biological function and in establishing a basis for targeted design efforts. Critical issues examined include the function of water molecules in providing strength and specificity of binding, the extent to which binding subsites are interdependent, and the roles of polypeptide chain flexibility and distal structural elements in contributing to specificity profiles. The studies also provide a foundation for exploring why specificity modification can be either straightforward or complex, depending on the particular system.     

The Role of Microsite Conditions in Restoring Trembling Aspen (Populus tremuloides Michx) from Seed

Encouraging natural regeneration of Populus tremuloides Michx (trembling aspen) from seed is a largely unexplored means for reintroducing the species into reclamation areas. We evaluated the effects of microsite (surface contour and substrate type) on aspen seedling establishment and growth on a reclaimed coal mine. The 4.6 ha study site was divided into six 48 m‐wide strips that had 15 or 40 cm capping material salvaged from a nearby forest floor added to the mine surface. We surveyed 126 m long transects located in the center of each strip for microsite conditions, and the presence and height of aspen seedlings. We found that aspen seedlings generally preferred mineral‐organic substrates and concave microsites. To facilitate the regeneration of aspen by seed, we suggest that land managers increase small‐scale roughness and microtopographic diversity on reclaimed sites .     

CyclinE-CDK2相关蛋白与细胞周期调控

细胞周期蛋白(cyclin)E和周期蛋白依赖性激酶(CDK)2的复合物CyclinE-CDK2为细胞从G1期进入S期的关键激酶复合物,在细胞从G1期进入S期过程中起着至关重要的作用.它通过磷酸化其下游一系列底物如Rb、CDC6、NPAT和P107等而使细胞启动DNA合成,从而使细胞不可逆转地进入S期.CyclinE-CDK2除了受到其下游RB/E2F通路的正调控外,同时也受细胞中其他一些因子的调控,如CIP/KIP家族蛋白的负调控作用,以及Skp2-SCF介导的泛素化降解作用等.     

Linking temperature sensitivity of soil organic matter decomposition to its molecular structure,accessibility, and microbial physiology

Temperature sensitivity of soil organic matter (SOM) decomposition may have a significant impact on global warming. Enzyme‐kinetic hypothesis suggests that decomposition of low‐quality substrate (recalcitrant molecular structure) requires higher activation energy and thus has greater temperature sensitivity than that of high‐quality, labile substrate. Supporting evidence, however, relies largely on indirect indices of substrate quality. Furthermore, the enzyme‐substrate reactions that drive decomposition may be regulated by microbial physiology and/or constrained by protective effects of soil mineral matrix. We thus tested the kinetic hypothesis by directly assessing the carbon molecular structure of low‐density fraction (LF) which represents readily accessible, mineral‐free SOM pool. Using five mineral soil samples of contrasting SOM concentrations, we conducted 30‐days incubations (15, 25, and 35 °C) to measure microbial respiration and quantified easily soluble C as well as microbial biomass C pools before and after the incubations. Carbon structure of LFs (<1.6 and 1.6–1.8 g cm^?3) and bulk soil was measured by solid‐state ¹³C‐NMR. Decomposition Q₁₀ was significantly correlated with the abundance of aromatic plus alkyl‐C relative to O‐alkyl‐C groups in LFs but not in bulk soil fraction or with the indirect C quality indices based on microbial respiration or biomass. The warming did not significantly change the concentration of biomass C or the three types of soluble C despite two‐ to three‐fold increase in respiration. Thus, enhanced microbial maintenance respiration (reduced C‐use efficiency) especially in the soils rich in recalcitrant LF might lead to the apparent equilibrium between SOM solubilization and microbial C uptake. Our results showed physical fractionation coupled with direct assessment of molecular structure as an effective approach and supported the enzyme‐kinetic interpretation of widely observed C quality‐temperature relationship for short‐term decomposition. Factors controlling long‐term decomposition Q₁₀ are more complex due to protective effect of mineral matrix and thus remain as a central question.     

利用机器学习提高M. jannaschii酪氨酰tRNA合成酶底物特异性分子建模预测的准确度

设计结合不同化学结构底物的酶结合袋是一个巨大的挑战. 传统的湿实验要筛选成千上万甚至上百万个突变体来寻找对特定配体结合的突变体,此过程需要耗费大量的时间和资源. 为了加快筛选过程,我们提出了一种新的工作流程,将分子建模和数据驱动的机器学习方法相结合,生成具有高富集率的突变文库,用于高效筛选能识别特定底物的蛋白质突变体. M. jannaschii酪氨酰tRNA合成酶（Mj. TyrRS）能识别特定的非天然氨基酸并催化形成氨酰tRNA,其不同的突变体能够识别不同结构的非天然氨基酸,并且已经有了许多报道和数据的积累,因此我们使用TyrRS作为一个例子来进行此筛选流程的概念验证. 基于已知的多个Mj. TyrRS的晶体结构及分子建模的结果,我们发现D158G/P是影响残基158~163位α螺旋蛋白骨架变化的关键突变. 我们的模拟结果表明,在含有687个突变体的测试数据中,与随机突变相比,分子建模和打分函数计算排序可以将目标突变体的富集率提高2倍,而使用已知突变体和对应的非天然氨基酸数据训练的机器学习模型进行校准后,筛选富集率可提高11倍. 这种分子建模和机器学习相结合的计算和筛选流程非常有助于Mj.TyrRS的底物特异性设计,可以大大减少湿实验的时间和成本. 此外,这种新方法在蛋白质计算设计领域具有广泛的应用前景.