Effect of Different Crowding Agents on the Architectural Properties of the Bacterial Nucleoid-Associated Protein HU

HU is a nucleoid-associated protein expressed in most eubacteria at a high amount of copies (tens of thousands). The protein is believed to bind across the genome to organize and compact the DNA. Most of the studies on HU have been carried out in a simple in vitro system, and to what extent these observations can be extrapolated to a living cell is unclear. In this study, we investigate the DNA binding properties of HU under conditions approximating physiological ones. We report that these properties are influenced by both macromolecular crowding and salt conditions. We use three different crowding agents (blotting grade blocker (BGB), bovine serum albumin (BSA), and polyethylene glycol 8000 (PEG8000)) as well as two different MgCl₂ conditions to mimic the intracellular environment. Using tethered particle motion (TPM), we show that the transition between two binding regimes, compaction and extension of the HU protein, is strongly affected by crowding agents. Our observations suggest that magnesium ions enhance the compaction of HU–DNA and suppress filamentation, while BGB and BSA increase the local concentration of the HU protein by more than 4-fold. Moreover, BGB and BSA seem to suppress filament formation. On the other hand, PEG8000 is not a good crowding agent for concentrations above 9% (w/v), because it might interact with DNA, the protein, and/or surfaces. Together, these results reveal a complex interplay between the HU protein and the various crowding agents that should be taken into consideration when using crowding agents to mimic an in vivo system.     

GLOBAL OPTIMIZATION OF PUMP CONFIGURATION PROBLEM USING EXTENDED CROWDING GENETIC ALGORITHM

An extended crowding genetic algorithm (ECGA) is introduced for solving optimal pumpconfiguration problem, which was presented by T.Westerlund in 1994. This problem has been found tobe non-convex, and the objective hation contained several local optima and global optimality couldnot be ensured by all the traditional MINLP optimization method. The concepts of species conservingand composite encoding are introduced to crowding genetic algorithm (CGA) for mantain the diver-sity of population more effectively and coping with the continuous and/or discrete variables in MINLPproblem. The solution of three-levels pump configuration got from DICOPT++ software (OA algo-rithm) is also given. By comparing with the solutions obtained from DICOPT++, ECP method, andMIN-MIN method, the ECGA algorithm proved to be very effective in finding the global optimalsolution of multi-levels pump configuration via using the problem-specific information.     

多目标进化算法中基于动态聚集距离的分布性保持策略 *

提出了基于动态聚集距离 ( DCD)的分布性保持策略 ,利用个体在不同维目标上聚集距离的差异程度来定义 DCD,并在种群维护中动态地计算 DCD。与目前经典算法 NSGA-II和ε -MOEA进行比较 ,实验结果表明 DCD能在较大程度上提高分布性 ,并得到较好的收敛性。     

基于档案交叉的动态多目标粒子群优化算法

为保证在动态环境中及时跟踪到最新的真实Pareto前沿,保持解集的均匀性,提出一种基于档案交叉的动态多目标粒子群优化算法。着重利用保存在外部档案的最新非劣解,对这些非劣解进行交叉操作以增加种群的多样性,促进档案中个体信息的交流;提出一种高效的欧氏拥挤距离策略,并将其应用于对外部档案的维护;修改粒子群算法模型使之更适用于动态多目标优化。实验结果表明,该算法能适应动态环境,快速跟踪动态Pareto面,解集均匀性良好。     

基于自适应学习的多目标粒子群优化算法

将进化算法应用于某些多目标优化问题时,采用增加种群规模和进化代数的方法往往耗费大量的目标函数计算开销,且达不到提高种群进化效率的目的,为此提出了一种基于自适应学习最优搜索方向的多目标粒子群优化算法。采用自适应惯性权值平衡算法的全局和局部搜索能力,采用聚类排挤方法保持Pareto非支配解集的分布均匀性,使用最近邻学习方法为每个粒子在Pareto非支配解集中寻找一个最优飞行目标来提高其收敛速度并保持粒子群搜索方向的多样性。实验结果表明,提出的算法可在显著地降低函数评估成本的前提下实现快速的搜索,并使粒子群均匀地逼近Pareto最优面。     

基于随机黑洞和逐步淘汰策略的多目标粒子群优化算法

提出一种基于随机黑洞粒子群算法(RBH-PSO) 和逐步淘汰策略的多目标粒子群优化(MRBHPSO-SE) 算法. 利用RBH-PSO 全局优化能力强和收敛速度快的优点逼近Pareto 最优解; 为了避免拥挤距离排序策略的缺陷, 提出逐步淘汰策略, 并将其应用到下一代粒子的选择策略中. 同时, 动态选择领导粒子, 运用动态惯性权重系数和变异操作 来增强种群全局寻优能力, 以及避免早熟收敛. 利用具有不同特点的测试函数进行验证, 结果表明, 与同类算法相比, 该算法具有较高的精度并兼顾优化解的多样性.

     

一种改进的小生境多目标粒子群优化算法

提出一种小生境多目标粒子群优化算法。使用环邻域拓扑且无需任何小生境参数,克服常规小生境技术中需确定小生境参数的困难。采用NSGA-II的非支配排序策略和动态加权方法选择最优粒子。基于拥挤度的变异操作引导粒子跳出局部最优,增强算法的全局搜索能力。通过对ZDT1~ZDT4和ZDT6的测试结果表明,与经典的多目标进化算法NSGA-II、PESA-II和MOPSO相比,该算法在最优解集的收敛度与多样性方面具有明显的优势。     

Immigration and location choices of native‐born workers in Canada

This paper investigates a possible crowding‐out effect of immigration in Canadian labour markets and explores how location choices of native‐born workers can be influenced by industry and occupation specific immigration clustering in both the potential destinations and the departure regions. We apply choice‐specific, clustered fixed‐effect response models. The results show that industry‐specific immigration clustering indices have strong and negative effects on the location choices of the native born. When the scaled immigration measures are used, the results confirm the ‘substitution’ hypothesis: native‐born workers who choose lower immigration in their destinations also move from the origins with higher immigration in their industry.     

Diverse Effects of Macromolecular Crowding on the Sequential Glycan‐Processing Pathway Involved in Glycoprotein Quality Control

Compared with in vitro conditions, the intracellular environment is highly crowded with biomolecules; this has numerous effects on protein functions, including enzymatic activity. We examined the effects of macromolecular crowding on glycan processing of N‐glycoprotein in the endoplasmic reticulum as a model sequential metabolic pathway. Experiments with synthetic substrates of physiological glycan structure clearly showed that the first half of the pathway (glucose trimming) was accelerated, whereas the second (mannose trimming) was decelerated under molecular crowding conditions. Furthermore, calreticulin, a lectin‐like molecular chaperone, bound more strongly to a glycan‐processing intermediate under these conditions. This study demonstrates the diverse effects of molecular crowding on sequential enzymatic processing, and the importance of the effects of macromolecular crowding on in vitro assays for understanding sequential metabolic pathways.