Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK₂) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.     

Identifying a Kinase Network Regulating FGF14:Nav1.6 Complex Assembly Using Split-Luciferase Complementation

Kinases play fundamental roles in the brain. Through complex signaling pathways, kinases regulate the strength of protein:protein interactions (PPI) influencing cell cycle, signal transduction, and electrical activity of neurons. Changes induced by kinases on neuronal excitability, synaptic plasticity and brain connectivity are linked to complex brain disorders, but the molecular mechanisms underlying these cellular events remain for the most part elusive. To further our understanding of brain disease, new methods for rapidly surveying kinase pathways in the cellular context are needed. The bioluminescence-based luciferase complementation assay (LCA) is a powerful, versatile toolkit for the exploration of PPI. LCA relies on the complementation of two firefly luciferase protein fragments that are functionally reconstituted into the full luciferase enzyme by two interacting binding partners. Here, we applied LCA in live cells to assay 12 kinase pathways as regulators of the PPI complex formed by the voltage-gated sodium channel, Nav1.6, a transmembrane ion channel that elicits the action potential in neurons and mediates synaptic transmission, and its multivalent accessory protein, the fibroblast growth factor 14 (FGF14). Through extensive dose-dependent validations of structurally-diverse kinase inhibitors and hierarchical clustering, we identified the PI3K/Akt pathway, the cell-cycle regulator Wee1 kinase, and protein kinase C (PKC) as prospective regulatory nodes of neuronal excitability through modulation of the FGF14:Nav1.6 complex. Ingenuity Pathway Analysis shows convergence of these pathways on glycogen synthase kinase 3 (GSK3) and functional assays demonstrate that inhibition of GSK3 impairs excitability of hippocampal neurons. This combined approach provides a versatile toolkit for rapidly surveying PPI signaling, allowing the discovery of new modular pathways centered on GSK3 that might be the basis for functional alterations between the normal and diseased brain.     

Modelling Infectious Hematopoietic Necrosis Virus Dispersion from Marine Salmon Farms in the Discovery Islands,British Columbia,Canada

Finite volume ocean circulation and particle tracking models are used to simulate water-borne transmission of infectious hematopoietic necrosis virus (IHNV) among Atlantic salmon (Salmo salar) farms in the Discovery Islands region of British Columbia, Canada. Historical simulations for April and July 2010 are carried out to demonstrate the seasonal impact of river discharge, wind, ultra-violet (UV) radiation, and heat flux conditions on near-surface currents, viral dispersion and survival. Numerical particles released from infected farm fish in accordance with IHNV shedding rates estimated through laboratory experiments are dispersed by model oceanic flows. Viral particles are inactivated by ambient UV radiation levels and by the natural microbial community at rates derived through laboratory studies. Viral concentration maps showing temporal and spatial changes are produced and combined with lab-determined minimum infectious dosages to estimate the infective connectivity among farms. Results demonstrate that neighbouring naïve farms can become exposed to IHNV via water-borne transport from an IHNV diseased farm, with a higher risk in April than July, and that many events in the sequence of farm outbreaks in 2001-2002 are consistent with higher risks in our farm connectivity matrix. Applications to other diseases, transfers between farmed and wild fish, and the effect of vaccinations are also discussed.     

Survival rates of mutant genes under artificial selection using individual and family information

We have used diffusion and branching process methods to investigate fixation rates, probabilities of survival per generation, and times to fixation of mutant genes under different selection methods incorporating individual and family information. Diffusion approximations fit well to simulated results even for large selection coefficients. Methods that give much weight to family information, such as BLUP evaluation which is widely used in animal breeding, reduce fixation rates of mutant genes because of the reduced effective population sizes. In general, it is observed that even mutants with relatively small heterozygous effects (say 0.1 phenotypic standard deviation) are practically ‘safe’ (i.e. their probability of loss from one generation to the next is smaller than, say, 10%) after just a few generations, typically less than 10. For methods of selection with larger effective size, such as within-family selection, the mutant is ‘safe’ in the population somewhat earlier but eventual fixation takes a longer time. Finally we evaluate the amount by which the use of marker assisted selection reduces the fixation probability of newly arisen mutants.     

人睫状神经营养因子的原核表达,纯化及其生物效应

人睫状神经营养因子（ｈＣＮＴＦ）克隆入ｐＢＶ２２０中，在ＤＨ５α菌株中表达，重组蛋白以包含体的形式存在，表达量为菌体总蛋白的５０％左右。经比较发现用２ｍｏｌ／Ｌ脲洗涤包含体可溶解大量可溶性细菌蛋白，且包含体损失较小。在高浓度变性剂条件下进行ｓｅｐｈａｒｃｙｌＳ－２００凝胶过滤，解决了纯化中ｈＣＮＴＦ易聚合的问题，在低浓度变性剂条件下进行ＤＥＡＥ离子交换，有利于蛋白活性的保持。经两步纯化后得到均一性ｈＣＮＴＦ，纯度达９５％以上。在自然状态下使ｈＣＮＴＦ复性。纯化复性后的ｈＣＮＴＦ对无血清培养的鸡胚背根节神经元和脊髓腹角运动神经元有明显的维持存活和促进生长发育的生物效应。     

城市景观生态风险评估框架与实践——以北京天坛地区为例

当前，城市景观生态风险研究缺少科学合理、方便实用的评估框架。作者基于景观生态风险评估基本范式，明确了城市景观生态服务价值的测算方法，分析了引起生态损害的自然因素和人类活动因素，形成了城市景观生态风险评估的技术框架和参数体系；继而以北京天坛地区为研究区，开展了典型城市景观生态风险的定量评估。结果表明：（1）天坛地区景观生态价值总量约为2.41亿元。区域的历史文化价值最高，教育和美学景观价值紧随其后。（2）城市景观生态受损概率呈现"北高南低"的空间分布格局。生态受损概率的高值区面积占整个区域总面积的22.2%，主要分布在珠市口、磁器口和崇文门附近区域。（3）城市景观生态风险呈现"北低南高"的空间分布格局。高风险区主要分布在天坛公园内的文物建筑周边。本研究提供了一个可参考的城市景观生态风险评估应用框架，对生态风险评估中的不确定性进行了讨论，研究针对天坛案例区的具体结论有助于城市管理者避免潜在的风险。