Pharmacokinetics of monoclonal antibodies and Fc-fusion proteins

There are many factors that can influence the pharmacokinetics (PK) of a mAb or Fc-fusion molecule with the primary determinant being FcRn-mediated recycling. Through Fab or Fc engineering, IgG-FcRn interaction can be used to generate a variety of therapeutic antibodies with significantly enhanced half-life or ability to remove unwanted antigen from circulation. Glycosylation of a mAb or Fc-fusion protein can have a significant impact on the PK of these molecules. mAb charge can be important and variants with pI values of 1–2 unit difference are likely to impact PK with lower pI values being favorable for a longer half-life. Most mAbs display target mediated drug disposition (TMDD), which can have significant consequences on the study designs of preclinical and clinical studies. The PK of mAb can also be influenced by anti-drug antibody (ADA) response and off-target binding, which require careful consideration during the discovery stage. mAbs are primarily absorbed through the lymphatics via convection and can be conveniently administered by the subcutaneous (sc) route in large doses/volumes with co-formulation of hyaluronidase. The human PK of a mAb can be reasonably estimated using cynomolgus monkey data and allometric scaling methods.     

Development of DNA-mediated transformation systems for plants

The genetic engineering of plants by DNA-mediated gene transfer requires that efficient transformation systems be developed. Considerable progress has been made in manipulating the Ti plasmid of Agrobacterium tumefaciens as a vehicle for delivery of foreign genes into protoplasts of dicotyle-donous plants. Part of the Ti plasmid, the T-DNA, can be incorporated into the genome of the host cell; the T-DNA can carry a foreign DNA sequence which co-integrates with it; under normal conditions, the tumorigenic-causing portion of the T-DNA can be inactivated so that transformed protoplasts can be regenerated and T-DNA with an inserted foreign gene can be stably maintained during regeneration, meiosis and gamete formation. A foreign gene has yet to be expressed in regenerated plants although a T-DNA gene for opine synthesis can function in regenerates. Developing a more ubiquitous transformation system for monocotyledons is further from fruition. Based on transformation systems for simple eukaryotic organisms, it is reasonable to expect that a DNA vector which is capable of amplifying a novel plant gene and which contains both a drug resistance marker to facilitate the selection of transformed plant protoplasts and a species-specific autonomously replicating sequence to ensure the stable maintenance of the input gene in the recipient cell can be constructed.     

The use of amplified fragment length polymorphism (AFLP) in the isolation of sex-specific markers

Sex identification is a problem in research and conservation. It can often be solved using a DNA test but this is only an option if a sex-specific marker is available. Such markers can be identified using the amplified fragment length polymorphism (AFLP) technique. This is usually a taxonomic method, as it produces a DNA fingerprint of 50-100 PCR bands. However, if male and female AFLP products are compared, sex-specific markers are confined to the heterogametic sex and can rapidly be identified. Once a marker is found, AFLP can be used to sex organisms directly or the marker can be sequenced and a standard PCR test designed.     

Biomimetics of Campaniform Sensilla： Measuring Strain from the Deformation of Holes

We present a bio-inspired strategy for designing embedded strain sensors in space structures. In insects, the campaniform sensillum is a hole extending through the cuticle arranged such that its shape changes in response to loads. The shape change is rotated through 90° by the suspension of a bell-shaped cap whose deflection is detected by a cell beneath the cuticle. It can be sensitive to displacements of the order of 1 nm. The essential morphology, a hole formed in a plate of fibrous composite mate- rial, was modelled by Skordos et al. who showed that global deformation of the plate （which can be flat, curved or a tube） induces higher local deformation of the hole due to its locally higher compliance. Further developments reported here show that this approach can be applied to groups of holes relative to their orientation. , The morphology of the sensillum in insects suggests that greater sensitivity can be achieved by arranging several holes in a regular pattern; that if the hole is oval it can be ＂aimed＂ to sense specific strain directions; and that either by controlling the shape of the hole or its relationship with other holes it can have a tuned response to dynamic strains. We investigate space applications in which novel bio-inspired strain sensors could successfully be used.     

Biomimetics of Campaniform Sensilla: Measuring Strain from the Deformation of Holes

We present a bio-inspired strategy for designing embedded strain sensors in space structures. In insects, the campaniform sensillum is a hole extending through the cuticle arranged such that its shape changes in response to loads. The shape change is rotated through 90 by the suspension of a bell-shaped cap whose deflection is detected by a cell beneath the cuticle. It can be sensitive to displacements of the order of 1 nm. The essential morphology, a hole formed in a plate of fibrous composite material, was modelled by Skordos et al. who showed that global deformation of the plate (which can be flat, curved or a tube) induces higher local deformation of the hole due to its locally higher compliance. Further developments reported here show that this approach can be applied to groups of holes relative to their orientation.The morphology of the sensillum in insects suggests that greater sensitivity can be achieved by arranging several holes in a regular pattern; that if the hole is oval it can be "aimed" to sense specific strain directions; and that either by controlling the shape of the hole or its relationship with other holes it can have a tuned response to dynamic strains.We investigate space applications in which novel bio-inspired strain sensors could successfully be used.     

Cationic liposome-mediated delivery of siRNAs in adult mice

RNA interference mediated by small interfering RNAs (siRNAs) is a powerful tool for dissecting gene function and drug target validation. siRNAs can be synthesized in large quantities and thus can be used to analyze a large number of sequences emerging from genome projects in a cost-effective manner. However, the major obstacle to the use of siRNAs as therapeutics is the difficulty involved in effective in vivo delivery. We used a fluorescein-labeled siRNA to investigate cationic liposome-mediated intravenous and intraperitoneal delivery in adult mice. We show that this simple approach can deliver siRNAs into various cell types. In addition, we show that in contrast to mouse cells, siRNAs can activate the non-specific pathway in human freshly isolated monocytes, resulting in TNF-alpha and IL-6 production. Taken together, the data provide a basis for lipid-mediated systemic delivery of siRNAs and indicate that certain siRNA sequences can activate the innate immunity response genes that can be beneficial for the treatment of cancer.     

Mechanism of gain modulation at single neuron and network levels

Gain modulation, in which the sensitivity of a neural response to one input is modified by a second input, is studied at single-neuron and network levels. At the single neuron level, gain modulation can arise if the two inputs are subject to a direct multiplicative interaction. Alternatively, these inputs can be summed in a linear manner by the neuron and gain modulation can arise, instead, from a nonlinear input–output relationship. We derive a mathematical constraint that can distinguish these two mechanisms even though they can look very similar, provided sufficient data of the appropriate type are available. Previously, it has been shown in coordinate transformation studies that artificial neurons with sigmoid transfer functions can acquire a nonlinear additive form of gain modulation through learning-driven adjustment of synaptic weights. We use the constraint derived for single-neuron studies to compare responses in this network with those of another network model based on a biologically inspired transfer function that can support approximately multiplicative interactions.     

Visual analysis of trabecular bone structure

Acquiring image data of bone biopsies by a micro-CT scanner is today a common technique. The amount of data to be assessed is huge. The task to assess quantitative measures requires a concise visualization. We present visualization techniques that can be used interactively on state-of-the-art PCs and demonstrate how the frontier can be pushed further. A skeletonization process is applied to the image of the bone to create the central surface. After triangulation this surface can be renderd at interactive frame rates. When the surface is additionally colored by local measures (mean grey value of image data, local thickness) the overall structure and details can be recognized at the same time. This can facilitate the exploration of the biopsy and can help finding special features.     

Application of atomic force microscopy to the study of micromechanical properties of biological materials

Atomic force microscopy (AFM) has been used to study the micromechanical properties of biological systems. Its unique ability to function both as an imaging device and force sensor with nanometer resolution in both gaseous and liquid environments has meant that AFM has provided unique insights into the mechanical behaviour of tissues, cells and single molecules. As a surface scanning device, AFM can map properties such as adhesion and the Young's modulus of surfaces. As a force sensor and nanoindentor AFM can directly measure properties such as the Young's modulus of surfaces or the binding forces of cells. As a stress-strain gauge AFM can study the stretching of single molecules or fibres and as a nanomanipulator it can dissect biological particles such as viruses or DNA strands. The present paper reviews key research that has demonstrated the versatility of AFM and how it can be exploited to study the micromechanical behaviour of biological materials.     

Biological significance of autoregulation through steady state analysis of genetic networks

Autoregulation of regulatory proteins is a recurring theme in genetic networks. Autoregulation is an important component of a genetic regulatory network besides protein-protein and protein-DNA interactions, stoichiometry, multiple binding sites and cooperativity. Although the biological significance of autoregulation has been studied before, its significance in presence of other mechanisms is not clearly enumerated. We have analyzed at steady state the significance of autoregulation in presence of other molecular mechanisms by considering hypothetical genetic networks. We demonstrate that autoregulation of a regulatory protein can impart amplification to the response. Further, autoregulation of an activator binding to the DNA as a dimer can introduce bistability, thus forcing the system to reside in two distinct steady states. In combination with autoregulation, cooperative binding can further increase the sensitivity and can yield a highly ultrasensitive response. We conclude that autoregulation with the help of other molecular mechanisms can impart distinct system level properties such as amplification, sensitivity and bistability. The results are further discussed in relation to various examples of genetic networks that exist in biological systems.     

microRNA在乙型肝炎病毒感染及相关疾病中的作用

乙型肝炎病毒(hepatitis B virus,HBV)是一种嗜肝性DNA病毒,感染后可导致急性和慢性肝炎,而慢性感染是导致肝硬化、肝癌和肝衰竭的主要病因。在乙型肝炎病毒复制、转录和相关疾病进程中,microRNA(miRNA)扮演着重要的角色。乙型肝炎病毒感染肝细胞后能引起细胞内microRNA表达谱的改变:一方面,microRNA能促进乙型肝炎病毒的转录和诱导宿主细胞向肿瘤细胞转化;另一方面,microRNA也能抑制乙型肝炎病毒包装和复制。重要的是,乙型肝炎病毒的感染能影响宿主血清microRNA的表达。因此,这类特殊的microRNA今后可成为乙型肝炎病毒相关疾病诊断的潜在生物标记物。将对乙型肝炎病毒与宿主microRNA之间相互作用及其相关生物学效应作一综述。     

Enhancement of tomogram interpretability using the locked self-rotation function

The interpretation of cryo-electron tomograms of macromolecular complexes can be difficult because of the large amount of noise and because of the missing wedge effect. Here it is shown how the presence of rotational symmetry in a sample can be utilized to enhance the quality of a tomographic analysis. The orientation of symmetry axes in a sub-tomogram can be determined using a locked self-rotation function. Given this knowledge, the sub-tomogram density can then be averaged to improve its interpretability. Sub-tomograms of the icosahedral bacteriophage phiX174 are used to demonstrate the procedure.     

Evolution of immunological memory and the regulation of competition between pathogens

Memory is a central characteristic of immune responses. It is defined as an elevated number of specific immune cells that remain after resolution of infection and can protect the host against reinfection. The evolution of immunological memory is subject to debate. The advantages of memory discussed so far include protection from reinfection, control of chronic infection, and the transfer of immune function to the next generation. Mathematical models are used to identify a new force that can drive the evolution of immunological memory: the duration of memory can regulate the degree of competition between different pathogens. While a long duration of memory provides lasting protection against reinfection, it may also allow an inferior pathogen species to persist. This can be detrimental for the host if the inferior pathogen is more virulent. On the other hand, a shorter duration of memory ensures that an inferior pathogen species is excluded. This can be beneficial for the host if the inferior pathogen is more virulent. Thus, while in the absence of pathogen diversity memory is always expected to evolve to a long duration, under specific circumstances, memory can evolve toward shorter durations in the presence of pathogen diversity.     

Fitness analyses of all possible point mutations for regions of genes in yeast

Deep sequencing can accurately measure the relative abundance of hundreds of mutations in a single bulk competition experiment, which can give a direct readout of the fitness of each mutant. Here we describe a protocol that we previously developed and optimized to measure the fitness effects of all possible individual codon substitutions for 10-aa regions of essential genes in yeast. Starting with a conditional strain (i.e., a temperature-sensitive strain), we describe how to efficiently generate plasmid libraries of point mutants that can then be transformed to generate libraries of yeast. The yeast libraries are competed under conditions that select for mutant function. Deep-sequencing analyses are used to determine the relative fitness of all mutants. This approach is faster and cheaper per mutant compared with analyzing individually isolated mutants. The protocol can be performed in ～4 weeks and many 10-aa regions can be analyzed in parallel.     

On the charge regulation of proteins

It is known that the overall charge of a protein can change as the molecule approaches a charged object like another protein or a cell membrane. We have formalized this mechanism using a statistical mechanical framework and show how this rather overlooked interaction increases the attraction between protein molecules. From the theory, we can identify a unique property, the protein charge capacitance, that contains all information needed to describe the charge regulation mechanism. The capacitance can be obtained from experiment or theory and is a function of pH, salt concentration, and the number of titrating residues. For a range of different protein molecules, we calculate the capacitance and demonstrate how it can be used to quantify the charge regulation interaction. With minimal effort, the derived formulas can be used to improve existing models by including a charge regulation term. Good agreement is found between theory, simulations, and experimental data.     

Prediction of oxidoreductase-catalyzed reactions based on atomic properties of metabolites

MOTIVATION: Our knowledge of metabolism is far from complete, and the gaps in our knowledge are being revealed by metabolomic detection of small-molecules not previously known to exist in cells. An important challenge is to determine the reactions in which these compounds participate, which can lead to the identification of gene products responsible for novel metabolic pathways. To address this challenge, we investigate how machine learning can be used to predict potential substrates and products of oxidoreductase-catalyzed reactions. RESULTS: We examined 1956 oxidation/reduction reactions in the KEGG database. The vast majority of these reactions (1626) can be divided into 12 subclasses, each of which is marked by a particular type of functional group transformation. For a given transformation, the local structures of reaction centers in substrates and products can be characterized by patterns. These patterns are not unique to reactants but are widely distributed among KEGG metabolites. To distinguish reactants from non-reactants, we trained classifiers (linear-kernel Support Vector Machines) using negative and positive examples. The input to a classifier is a set of atomic features that can be determined from the 2D chemical structure of a compound. Depending on the subclass of reaction, the accuracy of prediction for positives (negatives) is 64 to 93% (44 to 92%) when asking if a compound is a substrate and 71 to 98% (50 to 92%) when asking if a compound is a product. Sensitivity analysis reveals that this performance is robust to variations of the training data. Our results suggest that metabolic connectivity can be predicted with reasonable accuracy from the presence or absence of local structural motifs in compounds and their readily calculated atomic features. AVAILABILITY: Classifiers reported here can be used freely for noncommercial purposes via a Java program available upon request.     

Ginkgo: spatially-explicit simulator of complex phylogeographic histories

We present Ginkgo, a software package for agent-based, forward-time simulations of genealogies of multiple unlinked loci from diploid populations. Ginkgo simulates the evolution of one or more species on a spatially explicit landscape of cells. The user of the software can specify the geographical and environmental characteristics of the landscape, and these properties can change according to a prespecified schedule. The geographical elements modelled include the arrangement of cells and movement rates between particular cells. Each species has a function that can calculate a fitness score for any combination of an individual organism's phenotype and environmental characteristics. The user can control the number of fitness factors (the dimensionality of the cell-specific fitness factors and the individuals phenotypic vectors) and the weighting of each of these dimensions in the fitness calculation. Cell-specific fitness trait optima can be specified across the landscape to mimic differences in habitat. In addition to their differing fitness functions, species can differ in terms of their vagility and fecundity. Genealogies and occurrence data can be produced at any time during the simulation in NEXUS and ESRI Ascii Grid formats, respectively.     

基于DTW距离的DNA序列相似性分析

在DNA序列相似性的研究中,通常采用的动态规划算法对空位罚分函数缺乏理论依据而带有主观性,从而取得不同的结果,本文提出了一种基于DTW（Dynamic Time Warping,动态时间弯曲）距离的DNA序列相似性度量方法可以解决这一问题．通过DNA序列的图形表示把DNA序列转化为时间序列,然后计算DTW距离来度量序列相似度以表征DNA序列属性,得到能够比较DNA序列相似性度量方法,并用这个方法比较分析了七种东亚钳蝎神经毒素（Buthusmartensi Karsch neurotoxin）基因序列的相似性,验证了该度量方法的有效性和准确性．     

Visualization of dynamic simulations of muscle thin filaments

Following a novel computational formalism, the thin filament of muscle can be modeled by a computational machine containing a large number of finite automata that have one-to-one correspondence with the constituent protein molecules.¹ Computer graphics can be used to visualize the correspondence between the states of finite automata and the configurations of protein molecules according to the structural data. The dynamic simulation of the muscle filament that corresponds to the concurrent state transitions of finite automata can be represented as a sequence of video images. The kinetic and structural knowledge of individual protein molecules is, therefore, integrated into a coherent and functional system. This type of computation and visualization can also be useful for the investigation of molecular structure, function, and interaction in various complex biological systems.