Bridging the gap: From protein misfolding to protein misfolding diseases

Protein misfolding and aggregation are pathognomic for a number of the most common age-related degenerative diseases. Great progress has been made in studying protein aggregation in the test tube and also in replicating protein aggregation in vertebrate animal models of these diseases. However, we argue here that the development and effective integration of emerging techniques such as the methods of nanoscience and the use of invertebrate models are now providing powerful new opportunities to advance our current understanding of the fundamental origins of these disorders.     

Fluorescence Correlation Spectroscopy Measurements of the Membrane Protein TetA in Escherichia coli Suggest Rapid Diffusion at Short Length Scales

Structural inhomogeneities in biomembranes can lead to complex diffusive behavior of membrane proteins that depend on the length or time scales that are probed. This effect is well studied in eukaryotic cells, but has been explored only recently in bacteria. Here we used fluorescence recovery after photobleaching (FRAP) and fluorescence correlation spectroscopy (FCS) to study diffusion of the membrane protein TetA-YFP in E. coli. We find that the diffusion constant determined from FRAP is comparable to other reports of inner membrane protein diffusion constants in E. coli. However, FCS, which probes diffusion on shorter length scales, gives a value that is almost two orders of magnitude higher and is comparable to lipid diffusion constants. These results suggest there is a population of TetA-YFP molecules in the membrane that move rapidly over short length scales (∼ 400 nm) but move significantly more slowly over the longer length scales probed by FRAP.     

Molecular imaging: Bridging the gap between neuroradiology and neurohistology

Historically, in vivo imaging methods have largely relied on imaging gross anatomy. More recently it has become possible to depict biological processes at the cellular and molecular level. These new research methods use magnetic resonance imaging (MRI), positron emission tomography (PET), near-infrared optical imaging, scintigraphy, and autoradiography in vivo and in vitro. Of primary interest is the development of methods using MRI and PET with which the progress of gene therapy in glioblastoma (herpes simplex virus-thymidine kinase) and Parkinson's disease can be monitored and graphically displayed. The distribution of serotonin receptors in the human brain and the duration of serotonin-receptor antagonist binding can be assessed by PET. With PET, it is possible to localize neurofibrillary tangles (NFTs) and beta-amyloid senile plaques (APs) in the brains of living Alzheimer disease (AD) patients. MR tracking of transplanted oligodendrocyte progenitors is feasible for determining the extent of remyelinization in myelin-deficient rats. Stroke therapy in adult rats with subventricular zone cells can be monitored by MRI. Transgene expression (beta-galactosidase, tyrosinase, engineered transferrin receptor) can also be visualized using MRI. Macrophages can be marked with certain iron-containing contrast agents which, through accumulation at the margins of glioblastomas, ameliorate the visual demarcation in MRI. The use of near-infrared optical imaging techniques to visualize matrix-metalloproteinases and cathepsin B can improve the assessment of tumor aggressiveness and angiogenesis-inhibitory therapy. Apoptosis could be detected using near-infrared optical imaging representation of caspase 3 activity and annexin B. This review demonstrates the need for neurohistological research if further progress is to be made in the emerging but burgeoning field of molecular imaging.     

Bridging the gaps: From risk loci via non-coding RNAs to gene networks and prostate cancer phenotypes

Comment on: Glinskii AB, et al. Cell Cycle 2011; 10:3571-97.     

The Ability of Flux Balance Analysis to Predict Evolution of Central Metabolism Scales with the Initial Distance to the Optimum

The most powerful genome-scale framework to model metabolism, flux balance analysis (FBA), is an evolutionary optimality model. It hypothesizes selection upon a proposed optimality criterion in order to predict the set of internal fluxes that would maximize fitness. Here we present a direct test of the optimality assumption underlying FBA by comparing the central metabolic fluxes predicted by multiple criteria to changes measurable by a ¹³C-labeling method for experimentally-evolved strains. We considered datasets for three Escherichia coli evolution experiments that varied in their length, consistency of environment, and initial optimality. For ten populations that were evolved for 50,000 generations in glucose minimal medium, we observed modest changes in relative fluxes that led to small, but significant decreases in optimality and increased the distance to the predicted optimal flux distribution. In contrast, seven populations evolved on the poor substrate lactate for 900 generations collectively became more optimal and had flux distributions that moved toward predictions. For three pairs of central metabolic knockouts evolved on glucose for 600–800 generations, there was a balance between cases where optimality and flux patterns moved toward or away from FBA predictions. Despite this variation in predictability of changes in central metabolism, two generalities emerged. First, improved growth largely derived from evolved increases in the rate of substrate use. Second, FBA predictions bore out well for the two experiments initiated with ancestors with relatively sub-optimal yield, whereas those begun already quite optimal tended to move somewhat away from predictions. These findings suggest that the tradeoff between rate and yield is surprisingly modest. The observed positive correlation between rate and yield when adaptation initiated further from the optimum resulted in the ability of FBA to use stoichiometric constraints to predict the evolution of metabolism despite selection for rate.     

Tipping the Scale from Disorder to Alpha-helix: Folding of Amphiphilic Peptides in the Presence of Macroscopic and Molecular Interfaces

Secondary amphiphilicity is inherent to the secondary structural elements of proteins. By forming energetically favorable contacts with each other these amphiphilic building blocks give rise to the formation of a tertiary structure. Small proteins and peptides, on the other hand, are usually too short to form multiple structural elements and cannot stabilize them internally. Therefore, these molecules are often found to be structurally ambiguous up to the point of a large degree of intrinsic disorder in solution. Consequently, their conformational preference is particularly susceptible to environmental conditions such as pH, salts, or presence of interfaces. In this study we use molecular dynamics simulations to analyze the conformational behavior of two synthetic peptides, LKKLLKLLKKLLKL (LK) and EAALAEALAEALAE (EALA), with built-in secondary amphiphilicity upon forming an alpha-helix. We use these model peptides to systematically study their aggregation and the influence of macroscopic and molecular interfaces on their conformational preferences. We show that the peptides are neither random coils in bulk water nor fully formed alpha helices, but adopt multiple conformations and secondary structure elements with short lifetimes. These provide a basis for conformation-selection and population-shift upon environmental changes. Differences in these peptides’ response to macroscopic and molecular interfaces (presented by an aggregation partner) can be linked to their inherent alpha-helical tendencies in bulk water. We find that the peptides’ aggregation behavior is also strongly affected by presence or absence of an interface, and rather subtly depends on their surface charge and hydrophobicity.     

Molecular Ecology of Rotifers: From Population Differentiation to Speciation

The development of cost-effective molecular tools allowing the amplification of minute amounts of DNA effectively opened the field of molecular ecology for rotifers. Here I review these techniques and the advances they have provided in the understanding of sibling species complexes, clonal structure, resting egg banks, population structure, phylogeographic patterns and phylogenetic relationships in rotifers. Most of the research to date has focused on the rotifer species complex Brachionus plicatilis. The use of DNA sequence and microsatellite variation, in the context of the background knowledge of life history, mating behaviour, and temporal population dynamics in these organisms have revolutionised our views into the processes shaping the genetic diversity in aquatic invertebrates. Rotifers have populations with a very high number of clones in genetic equilibrium. In temporary populations clonal selection is effective in eroding the number of clones. Rotifer populations are strongly differentiated genetically for neutral markers, even at small geographical scales, and exhibit deep phylogeographic structure which might reflect the impact of Pleistocene glaciations. Despite the high potential for dispersal afforded by resting eggs, rotifers display persistent historical colonisation effects, with gene flow effective only at a local scale and with marked isolation by distance. Instances of long-distance transcontinental migration resulting in successful colonisation have also been revealed. B. plicatilis is composed of a group of several ancient species and sympatry is common. Despite this, the presence of cosmopolitan species in this species complex cannot be discounted. I discuss future priorities and point out the main areas where our knowledge is still insufficient.     

From Molecular to Process Simulation: Novel Approaches to the Prediction of Phase Equilibria and PVT Behavior Based on Molecular/Quantum Mechanics and Molecular Dynamics Simulations

Abstract

Actually, in modern process simulators, more than 75% of the code implemented is dedicated to physical properties estimation, calculation and predictions. Data banks storing pure component parameters and binary interaction parameters for phase equilibrium calculations are extensively used and continuously implemented in actual process simulators. This gives an idea of the important role physical properties availability plays in process simulation.

In this paper we propose a new way for coupling molecular and process simulation. The basic machinery is to resort to molecular/quantum mechanics and molecular dynamics simulation techniques for generating the parameters of some equations of state that will subsequently be used for the prediction of phase equilibria and PVT behavior of small and polymeric molecules as well. This information, in turn, will be used as input in the process simulator, thus creating a final and well-defined bridge between molecular and process simulations in chemical engineering.     

Phylogenetic Analysis and Molecular Evolution of Guanine Deaminases: From Guanine to Dendrites

Guanine deaminase (GDA; guanase) is a ubiquitous enzyme that catalyzes the first step of purine metabolism by hydrolytic deamination of guanine, resulting in the production of xanthine. This hydrolase subfamily member plays an essential role in maintaining homeostasis of cellular triphosphate nucleotides for energy, signal transduction pathways, and nitrogen sources. In mammals, GDA protein levels can play a role in neuronal development by regulating dendritic arborization. We previously demonstrated that the most abundant alternative splice form of GDA in mammals, termed cypin (cytosolic PSD-95 interactor), interacts with postsynaptic density proteins, regulates microtubule polymerization, and increases dendrite number. Since purine metabolism and dendrite development were previously thought to be independent cellular processes, this multifunctional protein serves as a new target for the treatment of cognitive disorders characterized by aberrant neuronal morphology and purine metabolism. Although the enzymatic activity of GDA has been conserved during evolution from prokaryotes to higher eukaryotes, a detailed evolutionary assessment of the principal domains in GDA proteins has not yet been put forward. In this study, we perform a complete evolutionary analysis of the full-length sequences and the principal domains in guanine deaminases. Furthermore, we reconstruct the molecular phylogeny of guanine deaminases with neighbor-joining, maximum-likelihood, and UPGMA methods of phylogenetic inference. This study can act as a model whereby a universal housekeeping enzyme may be adapted to act also as a key regulator of a developmental process.     

Phytoextraction of Zinc: Physiological and Molecular Mechanism

Zinc is an essential trace element, necessary for plants, animals, and microorganisms. Zn is required for many enzymes as a catalytic cofactor, for photosynthetic CO₂ fixation, and in maintaining the integrity of bio-membranes. However, Zn is potentially toxic when accumulated beyond cellular needs. Phytoextraction technique, which is a part of phytoremediation, has opened new avenues for remediation of Zn-contaminated places. Hyperaccumulators like Thlaspi caerulescens and Arabidopsis halleri have been identified, which can accumulate up to 40,000 mg kg^?1 Zn in the aerial parts of the plant body. Carboxylic acids, primarily malate, citrate, and oxalate, and amino acids are found to play an important role in Zn hyperaccumulation. Transmembrane metal transporters are assumed to play a key role in Zn metal uptake, xylem loading, and vacuolar sequestration. Members of CDF (cation diffusion facilitator) and ZIP (zinc-regulated transporter, iron-regulated transporter like protein) family have been implicated in Zn-metal-tolerance mechanisms. A potential metal-binding motif, containing multiple histidine residues, is found in the variable regions of almost all of the ZIP family, including ZIP1, ZIP2, ZIP4, ZRT1, and ZRT2. Overexpression of some Zn metal transporter genes like TcZNT1 (Thlaspi caerulescens Zn transporter1), TcHMA4 (Thlaspi caerulescens heavy metal ATPase) in Thlaspi caerulescens, AhMTP1;3 (Arabidopsis halleri metal transporter1;3) in Arabidopsis halleri, and PtdMTP1(Poplar metal transporter1) from a hybrid poplar confer Zn hypertolerance in Thlaspi, Arabidopsis, and Poplar plant species.     

Diffusion through a Double-Sided Plate: Development of a Method to Study Alga-Bacterium Interactions

Bacteria and algae isolated from a wastewater oxidation pond were inoculated onto opposing surfaces of double-layer agar plates (Lutri plates) to determine the usefulness of such plates for studying microbial interactions. The altered growth characteristics of various algae depending on the species of bacteria on the adjacent medium surface indicated that there was diffusion of extracellular products through the agar, suggesting that this simple assay can be used for screening potential interactions of actively growing organisms.     

Nanoscale Diblock Copolymer Micelles: Characterizations and Estimation of the Effective Diffusion Coefficients of Biomolecules Release through Cylindrical Diffusion Model

Biomolecules have been widely investigated as potential therapeutics for various diseases. However their use is limited due to rapid degradation and poor cellular uptake in vitro and in vivo. To address this issue, we synthesized a new nano-carrier system comprising of cholic acid-polyethylenimine (CA-PEI) copolymer micelles, via carbodiimide-mediated coupling for the efficient delivery of small interfering ribonucleic acid (siRNA) and bovine serum albumin (BSA) as model protein. The mean particle size of siRNA- or BSA-loaded CA-PEI micelles ranged from 100–150 nm, with zeta potentials of +3-+11 mV, respectively. Atomic force, transmission electron and field emission scanning electron microscopy demonstrated that the micelles exhibited excellent spherical morphology. No significant morphology or size changes were observed in the CA-PEI micelles after siRNA and BSA loading. CA-PEI micelles exhibited sustained release profile, the effective diffusion coefficients were successfully estimated using a mathematically-derived cylindrical diffusion model and the release data of siRNA and BSA closely fitted into this model. High siRNA and BSA binding and loading efficiencies (95% and 70%, respectively) were observed for CA-PEI micelles. Stability studies demonstrated that siRNA and BSA integrity was maintained after loading and release. The CA-PEI micelles were non cytotoxic to V79 and DLD-1 cells, as shown by alamarBlue and LIVE/DEAD cell viability assays. RT-PCR study revealed that siRNA-loaded CA-PEI micelles suppressed the mRNA for ABCB1 gene. These results revealed the promising potential of CA-PEI micelles as a stable, safe, and versatile nano-carrier for siRNA and the model protein delivery.