Gap junction-mimetic peptides do work, but in unexpected ways

Gap junction mimetic peptides containing sequences of the extracellular loops of connexins inhibit the de-novo formation of gap junction channels but do not impair the function of existing cell-cell channels. Recently, a flurry of publications appeared showing that such “GAP” peptides attenuate ATP release and/or surrogate measures of it. Although no direct effect on putative connexin “hemichannels” has ever been shown, the peptide effect has been used as diagnostic tool for demonstrating the existence of such channels. However, testing of the peptides on genuine unapposed membrane channels formed by connexins failed to reveal any inhibitory action of the peptides on channel activity. Instead, membrane channels formed by the unrelated pannexin1 were inhibited in the same concentration range as described for the release of ATP. Consequently, rather than indicating connexin involvement in ATP release, the GAP peptide effects represent supporting evidence for a role of pannexin1 in this process.     

Genetic Programming as a tool for identification of analyte-specificity from complex response patterns using a non-specific whole-cell biosensor

Whole-cell biosensors are mostly non-specific with respect to their detection capabilities for toxicants, and therefore offering an interesting perspective in environmental monitoring. However, to fully employ this feature, a robust classification method needs to be implemented into these sensor systems to allow further identification of detected substances. Substance-specific information can be extracted from signals derived from biosensors harbouring one or multiple biological components. Here, a major task is the identification of substance-specific information among considerable amounts of biosensor data. For this purpose, several approaches make use of statistical methods or machine learning algorithms. Genetic Programming (GP), a heuristic machine learning technique offers several advantages compared to other machine learning approaches and consequently may be a promising tool for biosensor data classification. In the present study, we have evaluated the use of GP for the classification of herbicides and herbicide classes (chemical classes) by analysis of substance-specific patterns derived from a whole-cell multi-species biosensor. We re-analysed data from a previously described array-based biosensor system employing diverse microalgae (Podola and Melkonian, 2005), aiming on the identification of five individual herbicides as well as two herbicide classes. GP analyses were performed using the commercially available GP software 'Discipulus', resulting in classifiers (computer programs) for the binary classification of each individual herbicide or herbicide class. GP-generated classifiers both for individual herbicides and herbicide classes were able to perform a statistically significant identification of herbicides or herbicide classes, respectively. The majority of classifiers were able to perform correct classifications (sensitivity) of about 80-95% of test data sets, whereas the false positive rate (specificity) was lower than 20% for most classifiers. Results suggest that a higher number of data sets may lead to a better classification performance. In the present paper, GP-based classification was combined with a biosensor for the first time. Our results demonstrate GP was able to identify substance-specific information within complex biosensor response patterns and furthermore use this information for successful toxicant classification in unknown samples. This suggests further research to assess perspectives and limitations of this approach in the field of biosensors.     

The distribution of water in native starch granules—a multinuclear NMR study

The microscopic distribution and dynamic state of water in native potato, maize and pea starch granules are investigated with NMR relaxometry and diffusometry. Besides extra-granular water, three water populations can be identified inside native potato starch granules. These are assigned to water in the amorphous growth rings; water in the semi-crystalline lamellae and “channel water”, which is located in the hexagonal channels within the B-type amylopectin crystals. The first two water populations are orientationally disordered and exchange with each other on a millisecond timescale at 290 K. NMR diffusometry shows that the water in packed granule beds is undergoing translational diffusion in a 2-dimensional space, either in thin layers between granules and/or in amorphous growth rings within the granules. The “channel water” is uniquely characterised by a 1 kHz deuterium doublet splitting and is in slow exchange with water in the other compartments on the NMR timescale. In the smaller maize granules all intra-granular water populations are in fast exchange and there is no evidence for “channel water” in the A-type crystal lattice. The NMR water proton and deuterium data for pea starch are consistent with a composite A and B-type crystal structure.     

Glucose biosensor based on nano-SiO2 and "unprotected" Pt nanoclusters

The “unprotected” Pt nanoclusters (average size 2 nm) mixed with the nanoscale SiO₂ particles (average size 13 nm) were used as a glucose oxidase immobilization carrier to fabricate the amperometric glucose biosensor. The bioactivity of glucose oxidase (GOx) immobilized on the composite was maintained and the as-prepared biosensor demonstrated high sensitivity (3.85 μA mM⁻¹) and good stability in glucose solution. The Pt–SiO₂ biosensor showed a detection limit of 1.5 μM with a linear range from 0.27 to 4.08 mM. In addition, the biosensor can be operated under wide pH range (pH 4.9–7.5) without great changes in its sensitivity. Cyclic voltammetry measurements showed a mixed controlled electrode reaction.     

Use of Label-free Optical Biosensors to Detect Modulation of Potassium Channels by G-protein Coupled Receptors

Ion channels control the electrical properties of neurons and other excitable cell types by selectively allowing ions to flow through the plasma membrane¹. To regulate neuronal excitability, the biophysical properties of ion channels are modified by signaling proteins and molecules, which often bind to the channels themselves to form a heteromeric channel complex^2,3. Traditional assays examining the interaction between channels and regulatory proteins require exogenous labels that can potentially alter the protein''s behavior and decrease the physiological relevance of the target, while providing little information on the time course of interactions in living cells. Optical biosensors, such as the X-BODY Biosciences BIND Scanner system, use a novel label-free technology, resonance wavelength grating (RWG) optical biosensors, to detect changes in resonant reflected light near the biosensor. This assay allows the detection of the relative change in mass within the bottom portion of living cells adherent to the biosensor surface resulting from ligand induced changes in cell adhesion and spreading, toxicity, proliferation, and changes in protein-protein interactions near the plasma membrane. RWG optical biosensors have been used to detect changes in mass near the plasma membrane of cells following activation of G protein-coupled receptors (GPCRs), receptor tyrosine kinases, and other cell surface receptors. Ligand-induced changes in ion channel-protein interactions can also be studied using this assay. In this paper, we will describe the experimental procedure used to detect the modulation of Slack-B sodium-activated potassium (K_Na) channels by GPCRs.     

A nanoparticle label/immunochromatographic electrochemical biosensor for rapid and sensitive detection of prostate-specific antigen

We present a nanoparticle (NP) label/immunochromatographic electrochemical biosensor (IEB) for rapid and sensitive detection of prostate-specific antigen (PSA) in human serum. This IEB integrates the immunochromatographic strip with the electrochemical detector for transducing quantitative signals. The NP label, made of CdSe@ZnS, serves as a signal-amplifier vehicle. A sandwich immunoreaction was performed on the immunochromatographic strip. The captured NP labels in the test zone were determined by highly sensitive stripping voltammetric measurement of the dissolved metallic component (cadmium) with a disposable-screen-printed electrode, which is embedded underneath the membrane of the test zone. Several experimental parameters (e.g., immunoreaction time, the amount of anti-PSA-NP conjugations applied) and electrochemical detection conditions (e.g., preconcentration potential and time) were optimized using this biosensor for PSA detection. The analytical performance of this biosensor was evaluated with serum PSA samples according to the “figure-of-merits” (e.g., dynamic range, reproducibility, and detection limit). The results were validated with enzyme-linked immunosorbent assay (ELISA) and showed high consistency. It is found that this biosensor is very sensitive with the detection limit of 0.02 ng mL⁻¹ PSA and is quite reproducible (with a relative standard deviation (R.S.D.) of 6.4%). This method is rapid, clinically practical, and less expensive than other diagnostic tools for PSA; therefore, this IEB coupled with a portable electrochemical analyzer shows great promise for simple, sensitive, quantitative point-of-care testing of disease-related protein biomarkers.     

Ecological communities: conceptual problems and definitions

Three major problems with respect to ecological communities are tackled. The first is the problem of ambiguity, i.e. the fact that the term “community” is being used for various kinds of objects at different levels of organisation. We argue that this problem can be resolved by restricting use of the term “community” to sets of co-occurring organisms belonging to a single taxonomic phylum or class (plants, birds, insects, etc.) and by using the term “biocoenosis” for sets of organisms belonging to multiple phyla or classes and comprising the biotic components of ecosystems. We also argue that interaction between organisms is neither a necessary nor a sufficient condition for community membership, or, in other words, that communities may consist of both interacting and non-interacting organisms. The second and third problems are the boundary problem and the problem of heterogeneity, i.e. the fact that communities, as currently defined, most often do not have discrete boundaries and are quite heterogeneous with respect to species composition. We argue that both problems result from the fact that communities are seen as groups of co-occurring populations of species, whereas actually populations of different species rarely if ever co-occur in exactly the same area. These problems can be resolved by redefining communities as particular sets of individuals occurring in the intersection of the areas occupied by different populations of species. In the final section we defend our definition against some potential objections, viz. (1) that it would lead to an excessive number of small communities, especially in species-rich situations, and (2) that, because population boundaries may change all the time, such communities would be very unstable.     

Modulation of a gated ion channel admittance in lipid bilayer membranes.

A future class of amperometric biosensors may utilize gated ion channels such as acetylcholine and glutamate receptors as chemical detection components. In this study, bilayer lipid membranes containing voltage-dependent anion channels (VDAC) were used to model an ion-channel-based biosensor which could continuously monitor AC amperometric changes resulting from induced changes in channel conductance. The in-phase and quadrature components of the induced alternating membrane current were monitored as a function of the applied DC offset voltage which was superimposed on the sinusoidal test voltage. The accuracy and sensitivity of the AC-measured VDAC response was dependent on the magnitude of the AC test voltage relative to the DC offset necessary for channel closure. The VDAC channel appears to be a suitable model protein for AC impedance-based biosensor fabrication.     

Discovery of novel sodium channel inhibitors—A gene family-based approach

Voltage-gated sodium (Na_V) channel inhibitors are an important class of drugs that are used to treat a number of CNS indications including pain, local anaesthesia, epilepsy and bipolar disorder. These drugs all have their origins in traditional “empirical” pharmacology, and it was only some time after discovery that they were found to inhibit Na_V channels. The basis for therapeutic selectivity of these drugs within different disease indications is currently unknown. However, the subsequent discovery of a multi-gene family of Na_V channels suggests a possible mechanism and has opened the way for more targeted approaches to finding improved therapeutic inhibitors. This article describes some ongoing approaches to systematically clone, express and characterise the entire family of Na_V subtypes in order to better understand their properties and define their individual physiological and pathophysiological roles. As well as providing specific disease validation for individual subtypes, this also provides a panel of reagents for comprehensively exploring the efficacy, selectivity and potency relationships of existing Na_V-blocking drugs. In this way, a gene family-based approach to Na_V channels has enabled a “drug-to-target” approach, reversing the more usual “gene-to-target-to-drug” paradigm. Together with recent advances in assay technology, gene family-based approaches are increasing the tractability of these targets and are re-invigorating Na_V drug discovery within the pharmaceutical industry.     

Survey of the year 2005 commercial optical biosensor literature

We identified 1113 articles (103 reviews, 1010 primary research articles) published in 2005 that describe experiments performed using commercially available optical biosensors. While this number of publications is impressive, we find that the quality of the biosensor work in these articles is often pretty poor. It is a little disappointing that there appears to be only a small set of researchers who know how to properly perform, analyze, and present biosensor data. To help focus the field, we spotlight work published by 10 research groups that exemplify the quality of data one should expect to see from a biosensor experiment. Also, in an effort to raise awareness of the common problems in the biosensor field, we provide side-by-side examples of good and bad data sets from the 2005 literature.     

Next-generation RNA-based fluorescent biosensors enable anaerobic detection of cyclic di-GMP

Bacteria occupy a diverse set of environmental niches with differing oxygen availability. Anaerobic environments such as mammalian digestive tracts and industrial reactors harbor an abundance of both obligate and facultative anaerobes, many of which play significant roles in human health and biomanufacturing. Studying bacterial function under partial or fully anaerobic conditions, however, is challenging given the paucity of suitable live-cell imaging tools. Here, we introduce a series of RNA-based fluorescent biosensors that respond selectively to cyclic di-GMP, an intracellular bacterial second messenger that controls cellular motility and biofilm formation. We demonstrate the utility of these biosensors in vivo under both aerobic and anaerobic conditions, and we show that biosensor expression does not interfere with the native motility phenotype. Together, our results attest to the effectiveness and versatility of RNA-based fluorescent biosensors, priming further development and application of these and other analogous sensors to study host–microbial and microbial–microbial interactions through small molecule signals.     

Construction of two <Emphasis Type="Italic">lux</Emphasis>-tagged Hg<Superscript>2+</Superscript>-specific biosensors and their luminescence performance

Two Hg2+-specific biosensors were constructed using bacterial luciferase as reporter gene and plasmid-free Pseudomonas putida X4 and Enterobacter aerogenes NTG-01 as host strains. The performance of X4 biosensor was compared with that of NTG-01 biosensor in the same assay conditions. The maximum bioluminescence for X4 (pmerRluxCDABE-Kan) biosensor was found during the midexponential phase and that for NTG-01 (pmerRluxCDABE-Kan) was at the late exponential phase. The shortest induction time of two biosensors was 30 min. The maximum light signal output for NTG-01 and X4 sensors was observed at the incubation time of 5 and 4 h, respectively. The lowest detectable concentration of mercury by the two biosensors were both of 100 pM at 28 degrees C, pH 7 and an initial cell number of 10(6) CFU ml(-1). Cd2+, Zn2+, Co2+, Cu2+, and Pb2 + ions at nanomolar level did not interfere with the measurement by the biosensors. These results show that the sensitivity of the two biosensors is sufficient for the detection of Hg2+ under most contaminated environments.     

Robustness and complexity co-constructed in multimodal signalling networks

In animal communication, signals are frequently emitted using different channels (e.g. frequencies in a vocalization) and different modalities (e.g. gestures can accompany vocalizations). We explore two explanations that have been provided for multimodality: (i) selection for high information transfer through dedicated channels and (ii) increasing fault tolerance or robustness through multichannel signals. Robustness relates to an accurate decoding of a signal when parts of a signal are occluded. We show analytically in simple feed-forward neural networks that while a multichannel signal can solve the robustness problem, a multimodal signal does so more effectively because it can maximize the contribution made by each channel while minimizing the effects of exclusion. Multimodality refers to sets of channels where within each set information is highly correlated. We show that the robustness property ensures correlations among channels producing complex, associative networks as a by-product. We refer to this as the principle of robust overdesign. We discuss the biological implications of this for the evolution of combinatorial signalling systems; in particular, how robustness promotes enough redundancy to allow for a subsequent specialization of redundant components into novel signals.     

The pet dogs ability for learning from a human demonstrator in a detour task is independent from the breed and age

There are many indications and much practical knowledge about the different tasks which various breeds of dogs are selected for. Correspondingly these different breeds are known to possess different physical and mental abilities. We hypothesized that commonly kept breeds will show differences in their problem solving ability in a detour task around a V-shaped fence, and also, that breed differences will affect their learning ability from a human demonstrator, who demonstrates a detour around the fence. Subjects were recruited in Hungarian pet dog schools. We compared the results of the 10 most common breeds in our sample when they were tested in the detour task without human demonstration. There was no significant difference between the latencies of detour, however, there was a trend that German Shepherd dogs were the quickest and Giant Schnauzers were the slowest in this test. For testing the social learning ability of dogs we formed three breed groups (“utility”, “shepherd” and “hunting”). There were no significant differences between these, all the breed groups learned equally well from the human demonstrator. However, we found that dogs belonging to the “shepherd” group looked back more frequently to their owner than the dogs in the “hunting” group. Further, we have found that the age of pet dogs did not affect their social learning ability in the detour task. Our results showed that the pet status of a dog has probably a stronger effect on its cognitive performance and human related behaviour than its age or breed. These results emphasize that socialization and common activities with the dog might overcome the possible breed differences, if we give the dogs common problem solving, or social learning tasks.     

Membrane Trafficking of Large Conductance Calcium-activated Potassium Channels Is Regulated by Alternative Splicing of a Transplantable, Acidic Trafficking Motif in the RCK1-RCK2 Linker

Trafficking of the pore-forming α-subunits of large conductance calcium- and voltage-activated potassium (BK) channels to the cell surface represents an important regulatory step in controlling BK channel function. Here, we identify multiple trafficking signals within the intracellular RCK1-RCK2 linker of the cytosolic C terminus of the channel that are required for efficient cell surface expression of the channel. In particular, an acidic cluster-like motif was essential for channel exit from the endoplasmic reticulum and subsequent cell surface expression. This motif could be transplanted onto a heterologous nonchannel protein to enhance cell surface expression by accelerating endoplasmic reticulum export. Importantly, we identified a human alternatively spliced BK channel variant, hSloΔ_579–664, in which these trafficking signals are excluded because of in-frame exon skipping. The hSloΔ_579–664 variant is expressed in multiple human tissues and cannot form functional channels at the cell surface even though it retains the putative RCK domains and downstream trafficking signals. Functionally, the hSloΔ_579–664 variant acts as a dominant negative subunit to suppress cell surface expression of BK channels. Thus alternative splicing of the intracellular RCK1-RCK2 linker plays a critical role in determining cell surface expression of BK channels by controlling the inclusion/exclusion of multiple trafficking motifs.     

Array biosensor based on enzyme kinetics monitoring by fluorescence spectroscopy: application for neurotoxins detection

The aim of the present work is to develop an evanescence wave array biosensor exploiting the “kinetic” approach of enzymatic reaction and further detection of the reaction products via pH sensitive fluorophore reporter. To demonstrate the feasibility of this approach, we have developed a biosensor array with the potential for direct detection of organophosphates using as a biorecognition element, an enzyme organophosphorus hydrolase (OPH), conjugated with a pH-sensitive fluorophore, carboxynaphthofluorescein (CNF). The presence of reference spots allows the discrimination of the enzymatic and non-enzymatic based pH changes; bovine serum albumin (BSA) was used as a non-enzymatic scaffold protein for CNF attachment at the reference spots. An array biosensor unit developed at the Naval Research Laboratories (NRL) was adopted as the detection platform and appropriately modified for enzyme-based measurements. A planar multi-mode waveguide was covered with an optically transparent TiO₂ layer to increase the surface area available for immobilization.

The biosensor enabled the detection of 2.5 μM paraoxon, and 10 μM DFP and parathion, respectively. Very short response time of 30 s can be achieved with a total analysis time of less than 2 min. When operated at room temperature and stored at 4 °C, the waveguide retained reasonable activity for greater than 45 days.     

Non-similarity combinatorial problems

Similarity problems intensively investigated in computational molecular biology have the following two stringology models: find the longest string included in any string of a given finite language, and find the shortest string including every string of a given finite language. These two problems are exemplified by the two well-known pairs of problems, the longest common subsequence (or substring) problem and the shortest common supersequence (or superstring) problem. interpretations.

In this paper we consider opposite problems connected with string non-inclusion relations: find the shortest string included in no string of a given finite language and find the longest string including no string of a given finite language. The predicate “string is not included in string β” is interpreted either as “ is not a subsequence of β” or as “ is not a substring of β”. The main purpose is to determine the complexity status of the non-similarity problems. Using graph approaches, we present NP-hardness proofs for the first interpretation and polynomial-time algorithms for the second one. Special cases of the problems, and related issues are discussed.     

A versatile biosensor device for continuous biomedical monitoring

Although biosensors are by means suitable for continuous biomedical monitoring, due to fouling and blood clotting, in vivo performance is far from optimal. For this reason, ultrafiltration, microdialysis or open tubular flow is frequently used as interface. To secure quantitative recoveries of the analyte of interest, sampling at submicrolitre level will be necessary which in turn necessitates the development of small and versatile biosensor devices. Here, a miniaturised biosensor device, which directly can be connected to various interfaces will be presented. The biosensor device consists of a pulsefree pump and a biosensor with an internal volume of 10–20 nl. In this article, the production as well as the construction of the flow-through cell of the biosensor will be discussed. The advantages and disadvantages of several production processes will be demonstrated and a detailed protocol for the production of such a nanoliter flow-through cell will be presented. With respect to the bio-selector, several permselective membranes have been tested on their performance characteristics. Results obtained with these biosensors will be presented and discussed. Finally, a protocol based upon in situ electropolymerisation for the immobilisation of the biological component was defined and several biosensors based upon this principle have been produced and tested for the monitoring of glucose respectively lactate. To demonstrate, data obtained during a variety of in vivo studies at different clinical relevant applications will be presented.