Membrane-destabilizing activity of pH-responsive cationic lysine-based surfactants: role of charge position and alkyl chain length

Many strategies for treating diseases require the delivery of drugs into the cell cytoplasm following internalization within endosomal vesicles. Thus, compounds triggered by low pH to disrupt membranes and release endosomal contents into the cytosol are of particular interest. Here, we report novel cationic lysine-based surfactants (hydrochloride salts of N¿- and N¿-acyl lysine methyl ester) that differ in the position of the positive charge and the length of the alkyl chain. Amino acid-based surfactants could be promising novel biomaterials in drug delivery systems, given their biocompatible properties and low cytotoxic potential. We examined their ability to disrupt the cell membrane in a range of pH values, concentrations and incubation times, using a standard hemolysis assay as a model of endosomal membranes. Furthermore, we addressed the mechanism of surfactant-mediated membrane destabilization, including the effects of each surfactant on erythrocyte morphology as a function of pH. We found that only surfactants with the positive charge on the ¿-amino group of lysine showed pH-sensitive hemolytic activity and improved kinetics within the endosomal pH range, indicating that the positive charge position is critical for pH-responsive behavior. Moreover, our results showed that an increase in the alkyl chain length from 14 to 16 carbon atoms was associated with a lower ability to disrupt cell membranes. Knowledge on modulating surfactant-lipid bilayer interactions may help us to develop more efficient biocompatible amino acid-based drug delivery devices.

Insertion of a malE B-Galactosidase fusion protein into the envelope of Escherichia coli disrupts biogenesis of outer membrane proteins and processing of inner membrane proteins

The synthesis of a membrane-bound MalE ,B-galactosidase hybrid protein, when induced by growth of Escherichia coli on maltose, leads to inhibition of cell division and eventually a reduced rate of mass increase. In addition, the relative rate of synthesis of outer membrane proteins, but not that of inner membrane proteins, was reduced by about 50%o. Kinetic experiments demonstrated that this reduction coincided with the period of maximum synthesis of the hybrid protein (and another maltose-inducible protein, LamB). The accumulation of this abnormal protein in the envelope therefore appeared specifically to inhibit the synthesis, the assembly of outer membrane proteins, or both, indicating that the hybrid protein blocks some export site or causes the sequestration of some limiting factor(s) involved in the export process. Since the MalE protein is normally located in the periplasm, the results also suggest that the synthesis of periplasmic and outer membrane proteins may involve some steps in common. The reduced rate of synthesis of outer membrane proteins was also accompanied by the accumulation in the envelope of at least one outer membrane protein and at least two inner membrane proteins as higher-molecular-weight forms, indicating that processing (removal of the N-terminal signal sequence) was also disrupted by the presence of the hybrid protein. These results may indicate that the assembly of these membrane proteins is blocked at a relatively late step rather than at the level of primary recognition of some site by the signal sequence. In addition, the results suggest that some step common to the biogenesis of quite different kinds of envelope protein is blocked by the presence of the hybrid protein.

Grape epicatechin conjugates prevent erythrocyte membrane protein oxidation

Epicatechin conjugates obtained from grape have shown antioxidant activity in various systems. However, how these conjugates exert their antioxidant benefits has not been widely studied. We assessed the activity of epicatechin and epicatechin conjugates on the erythrocyte membrane in the presence and absence of a peroxyl radical initiator, to increase our understanding of their mechanisms. Thus, we studied cell membrane fluidity by fluorescence anisotropy measurements, morphology of erythrocytes by scanning electron microscopy, and finally, red cell membrane proteins by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Our data showed that incubation of red cells in the presence of epicatechin derivatives altered membrane fluidity and erythrocyte morphology but not the membrane protein pattern. The presence in the medium of the peroxyl radical initiator 2,2′-azobis(amidinopropane) dihydrochloride (AAPH) resulted in membrane disruptions at all levels analyzed, causing changes in membrane fluidity, cell morphology, and protein degradation. The presence of antioxidants avoided protein oxidation, indicating that the interaction of epicatechin conjugates with the lipid bilayer might reduce the accessibility of AAPH to membranes, which could explain in part the inhibitory ability of these compounds against hemolysis induced by peroxidative insult.

Phospholipid bilayer perturbing-properties underlying lysis induced by pH-sensitive cationic lysine-based surfactants in biomembranes

Many strategies for treating diseases require the delivery of drugs into the cell cytoplasm following internalization within endosomal vesicles. Thus, compounds triggered by low pH to disrupt membranes and release endosomal contents into the cytosol are of particular interest. Here, we report novel cationic lysine-based surfactants (hydrochloride salts of Nε- and Nα-acyl lysine methyl ester) that differ in the position of the positive charge and the length of the alkyl chain. Amino acid-based surfactants could be promising novel biomaterials in drug delivery systems, given their biocompatible properties and low cytotoxic potential. We examined their ability to disrupt the cell membrane in a range of pH values, concentrations and incubation times, using a standard hemolysis assay as a model of endosomal membranes. Furthermore, we addressed the mechanism of surfactant-mediated membrane destabilization, including the effects of each surfactant on erythrocyte morphology as a function of pH. We found that only surfactants with the positive charge on the α-amino group of lysine showed pH-sensitive hemolytic activity and improved kinetics within the endosomal pH range, indicating that the positive charge position is critical for pH-responsive behavior. Moreover, our results showed that an increase in the alkyl chain length from 14 to 16 carbon atoms was associated with a lower ability to disrupt cell membranes. Knowledge on modulating surfactant-lipid bilayer interactions may help us to develop more efficient biocompatible amino acid-based drug delivery devices.

Outer membrane vesicles from cold-adapted antarctic bacteria

Many Gram-negative, cold-adapted bacteria from the Antarctic environment produce large amounts of extracellular matter with potential biotechnological applications. Transmission electron microscopy (TEM) analysis after high-pressure freezing and freeze substitution (HPF-FS) showed that this extracellular matter is structurally complex, appearing around cells as a netlike mesh, and composed of an exopolymeric substance (EPS) containing large numbers of outer membrane vesicles (OMVs). Isolation, purification and protein profiling via 1D SDS-PAGE confirmed the outer membrane origin of these Antarctic bacteria OMVs. In an initial attempt to elucidate the role of OMVs in cold-adapted strains of Gram-negative bacteria, a proteomic analysis demonstrated that they were highly enriched in outer membrane proteins and periplasmic proteins associated with nutrient processing and transport, suggesting that the OMVs may be involved in nutrient sensing and bacterial survival. OMVs from Gram-negative bacteria are known to play a role in lateral DNA transfer, but the presence of DNA in these vesicles has remained difficult to explain. A structural study of Shewanella vesiculosa M7T using TEM and Cryo-TEM revealed that this Antarctic Gram-negative bacterium naturally releases conventional one-bilayer OMVs, together with a more complex type of OMV, previously undescribed, which on formation drags along inner membrane and cytoplasmic content and can therefore also entrap DNA.

Outer membrane vesicles from cold-adapted antarctic bacteria

Many Gram-negative, cold-adapted bacteria from the Antarctic environment produce large amounts of extracellular matter with potential biotechnological applications. Transmission electron microscopy (TEM) analysis after high-pressure freezing and freeze substitution (HPF-FS) showed that this extracellular matter is structurally complex, appearing around cells as a netlike mesh, and composed of an exopolymeric substance (EPS) containing large numbers of outer membrane vesicles (OMVs). Isolation, purification and protein profiling via 1D SDS-PAGE confirmed the outer membrane origin of these Antarctic bacteria OMVs. In an initial attempt to elucidate the role of OMVs in cold-adapted strains of Gram-negative bacteria, a proteomic analysis demonstrated that they were highly enriched in outer membrane proteins and periplasmic proteins associated with nutrient processing and transport, suggesting that the OMVs may be involved in nutrient sensing and bacterial survival. OMVs from Gram-negative bacteria are known to play a role in lateral DNA transfer, but the presence of DNA in these vesicles has remained difficult to explain. A structural study of Shewanella vesiculosa M7T using TEM and Cryo-TEM revealed that this Antarctic Gram-negative bacterium naturally releases conventional one-bilayer OMVs, together with a more complex type of OMV, previously undescribed, which on formation drags along inner membrane and cytoplasmic content and can therefore also entrap DNA.

Dual Action of BPC194: A Membrane Active Peptide Killing Bacterial Cells

Membrane active peptides can perturb the lipid bilayer in several ways, such as poration and fusion of the target cell membrane, and thereby efficiently kill bacterial cells. We probe here the mechanistic basis of membrane poration and fusion caused by membrane-active, antimicrobial peptides. We show that the cyclic antimicrobial peptide, BPC194, inhibits growth of Gram-negative bacteria and ruptures the outer and inner membrane at the onset of killing, suggesting that not just poration is taking place at the cell envelope. To simplify the system and to better understand the mechanism of action, we performed Förster resonance energy transfer and cryogenic transmission electron microscopy studies in model membranes and show that the BPC194 causes fusion of vesicles. The fusogenic action is accompanied by leakage as probed by dual-color fluorescence burst analysis at a single liposome level. Atomistic molecular dynamics simulations reveal how the peptides are able to simultaneously perturb the membrane towards porated and fused states. We show that the cyclic antimicrobial peptides trigger both fusion and pore formation and that such large membrane perturbations have a similar mechanistic basis

Preliminary study of cooperation in hybrid ad-hoc networks

In this paper, we present a first approach to evolve a cooperative behavior in ad hoc networks. Since wireless nodes are energy constrained, it may not be in the best interest of a node to always accept relay requests. On the other hand, if all nodes decide not to expend energy in relaying, then network throughput will drop dramatically. Both these extreme scenarios are unfavorable to the interests of a user. In this paper we deal with the issue of user cooperation in ad hoc networks by developing the algorithm called Generous Tit-For-Tat. We assume that nodes are rational, i.e., their actions are strictly determined by self-interest, and that each node is associated with a minimum lifetime constraint. Given these lifetime constraints and the assumption of rational behavior, we study the added behavior of the network.

Textural classification of land cover using support vector machines: an empirical comparison with parametric, non parametric and hybrid classifiers in the Bolivian Amazon

Land cover classification is a key research field in remote sensing and land change science as thematic maps derived from remotely sensed data have become the basis for analyzing many socio-ecological issues. However, land cover classification remains a difficult task and it is especially challenging in heterogeneous tropical landscapes where nonetheless such maps are of great importance. The present study aims to establish an efficient classification approach to accurately map all broad land cover classes in a large, heterogeneous tropical area of Bolivia, as a basis for further studies (e.g., land cover-land use change). Specifically, we compare the performance of parametric (maximum likelihood), non-parametric (k-nearest neighbour and four different support vector machines - SVM), and hybrid classifiers, using both hard and soft (fuzzy) accuracy assessments. In addition, we test whether the inclusion of a textural index (homogeneity) in the classifications improves their performance. We classified Landsat imagery for two dates corresponding to dry and wet seasons and found that non-parametric, and particularly SVM classifiers, outperformed both parametric and hybrid classifiers. We also found that the use of the homogeneity index along with reflectance bands significantly increased the overall accuracy of all the classifications, but particularly of SVM algorithms. We observed that improvements in producer’s and user’s accuracies through the inclusion of the homogeneity index were different depending on land cover classes. Earlygrowth/degraded forests, pastures, grasslands and savanna were the classes most improved, especially with the SVM radial basis function and SVM sigmoid classifiers, though with both classifiers all land cover classes were mapped with producer’s and user’s accuracies of around 90%. Our approach seems very well suited to accurately map land cover in tropical regions, thus having the potential to contribute to conservation initiatives, climate change mitigation schemes such as REDD+, and rural development policies.

Merging the hypothetical extraction method and the classical multiplier approach: a hybrid possibility for identifying key distributive sectors

The two main alternative methods used to identify key sectors within the input-output approach, the Classical Multiplier method (CMM) and the Hypothetical Extraction method (HEM), are formally and empirically compared in this paper. Our findings indicate that the main distinction between the two approaches stems from the role of the internal effects. These internal effects are quantified under the CMM while under the HEM only external impacts are considered. In our comparison, we find, however that CMM backward measures are more influenced by within-block effects than the proposed forward indices under this approach. The conclusions of this comparison allow us to develop a hybrid proposal that combines these two existing approaches. This hybrid model has the advantage of making it possible to distinguish and disaggregate external effects from those that a purely internal. This proposal has also an additional interest in terms of policy implications. Indeed, the hybrid approach may provide useful information for the design of ''second best'' stimulus policies that aim at a more balanced perspective between overall economy-wide impacts and their sectoral distribution.

An hybrid methodology for RL-based behavior coordination in a target following mission with an AUV

Proposes a behavior-based scheme for high-level control of autonomous underwater vehicles (AUVs). Two main characteristics can be highlighted in the control scheme. Behavior coordination is done through a hybrid methodology, which takes in advantages of the robustness and modularity in competitive approaches, as well as optimized trajectories

Scene Classification Using a Hybrid Generative/Discriminative Approach

We investigate whether dimensionality reduction using a latent generative model is beneficial for the task of weakly supervised scene classification. In detail, we are given a set of labeled images of scenes (for example, coast, forest, city, river, etc.), and our objective is to classify a new image into one of these categories. Our approach consists of first discovering latent ";topics"; using probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature here applied to a bag of visual words representation for each image, and subsequently, training a multiway classifier on the topic distribution vector for each image. We compare this approach to that of representing each image by a bag of visual words vector directly and training a multiway classifier on these vectors. To this end, we introduce a novel vocabulary using dense color SIFT descriptors and then investigate the classification performance under changes in the size of the visual vocabulary, the number of latent topics learned, and the type of discriminative classifier used (k-nearest neighbor or SVM). We achieve superior classification performance to recent publications that have used a bag of visual word representation, in all cases, using the authors' own data sets and testing protocols. We also investigate the gain in adding spatial information. We show applications to image retrieval with relevance feedback and to scene classification in videos

Hybrid coordination of reinforcement learning-based behaviors for AUV control

This paper proposes a hybrid coordination method for behavior-based control architectures. The hybrid method takes advantages of the robustness and modularity in competitive approaches as well as optimized trajectories in cooperative ones. This paper shows the feasibility of applying this hybrid method with a 3D-navigation to an autonomous underwater vehicle (AUV). The behaviors are learnt online by means of reinforcement learning. A continuous Q-learning implemented with a feed-forward neural network is employed. Realistic simulations were carried out. The results obtained show the good performance of the hybrid method on behavior coordination as well as the convergence of the behaviors

A hybrid method for sag source location in power network

The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification

Modeling of hybrid systems by piecewise decomposition

Piecewise linear models systems arise as mathematical models of systems in many practical applications, often from linearization for nonlinear systems. There are two main approaches of dealing with these systems according to their continuous or discrete-time aspects. We propose an approach which is based on the state transformation, more particularly the partition of the phase portrait in different regions where each subregion is modeled as a two-dimensional linear time invariant system. Then the Takagi-Sugeno model, which is a combination of local model is calculated. The simulation results show that the Alpha partition is well-suited for dealing with such a system