Impedimetric sensor of bacterial toxins based on mixed (Concanavalin A)/polyaniline films

Antigen-Mimic Nanoparticles in Ultrasensitive on-Chip Integrated Anti-p53 Antibody Quantification

As a tumor-suppressing protein, p53 plays a crucial role in preventing cancer development. Its utility as an early cancer detection tool is significant, potentially enabling clinicians to forestall disease advancement and improve patient prognosis. In response to the pathological overexpression of this antigen in tumors, the prevalence of anti-p53 antibodies increases in serum, in a manner quantitatively indicative of cancer progression. This spike can be detected through techniques, such as Western blotting, immunohistochemistry, and immunoprecipitation. In this study, we present an electrochemical approach that supports ultrasensitive and highly selective anti-p53 autoantibody quantification without the use of an immuno-modified electrode. We specifically employ antigen-mimicking and antibody-capturing peptide-coated magnetic nanoparticles, along with an AC magnetic field-promoted sample mixing, prior to the presentation of Fab-captured targets to simple lectin-modified sensors. The subfemtomolar assays are highly selective and support quantification from serum-spiked samples within minutes.

3D Impedimetric Biosensor for Cyanobacteria Detection in Natural Water Sources

The excessive growth of cyanobacteria in freshwater sources produces the development of toxic blooms mainly due to the production of cyanotoxins. Here, a novel impedimetric biosensor based on a three-dimensional interdigitated electrode array (3D-IDEA) for detection of cyanobacteria cells is reported. The 3D-IDEA sensor surface biofunctionalization was performed by means of the layer-by-layer method using polyethyleneimine (PEI) as the anchoring layer and concanavalin A (Con A) as the bioreceptor to lipopolysaccharides of cyanobacteria cells. The developed PEI-Con A 3D-IDEA sensors show a linear response (R2 = 0.992) of the impedance changes (RS) versus the logarithm of cyanobacteria concentrations in the range of 102–105 cells·mL−1 with the detection limit of 100 cells·mL−1. Moreover, to prevent the interference from components that may be present in real water samples and minimize a possible sample matrix effect, a filtration methodology to recover cyanobacterial cells was developed. The proposed methodology allows 91.2% bacteria recovery, permitting to obtain results similar to controlled assays. The developed system can be used in aquatic environments to detect cyanobacteria and consequently to prevent the formation of blooms and the production of cyanotoxins. Con A can bind to most polysaccharides and so react with other types of bacteria. However, currently, on the market, it is not possible to find specific biorecognition elements for cyanobacteria. Taking into consideration the specificity of samples to be analyzed (natural water resources), it is difficult to expect high concentration of other bacteria. In this sense, the developed methodology may be used as an alarm system to select samples for more thorough and precise laboratory analysis.

Using machine learning and liquid crystal droplets to identify and quantify endotoxins from different bacterial species

Detection and quantification of bacterial endotoxins is important in a range of health-related contexts, including during pharmaceutical manufacturing of therapeutic proteins and vaccines. Here we combine experimental measurements based on nematic liquid crystalline droplets and machine learning methods to show that it is possible to classify bacterial sources (Escherichia coli, Pseudomonas aeruginosa, Salmonella minnesota) and quantify concentration of endotoxin derived from all three bacterial species present in aqueous solution. The approach uses flow cytometry to quantify, in a high-throughput manner, changes in the internal ordering of micrometer-sized droplets of nematic 4-cyano-4'-pentylbiphenyl triggered by the endotoxins. The changes in internal ordering alter the intensities of light side-scattered (SSC, large-angle) and forward-scattered (FSC, small-angle) by the liquid crystal droplets. A convolutional neural network (Endonet) is trained using the large data sets generated by flow cytometry and shown to predict endotoxin source and concentration directly from the FSC/SSC scatter plots. By using saliency maps, we reveal how EndoNet captures subtle differences in scatter fields to enable classification of bacterial source and quantification of endotoxin concentration over a range that spans eight orders of magnitude (0.01 pg mL-1 to 1 μg mL-1). We attribute changes in scatter fields with bacterial origin of endotoxin, as detected by EndoNet, to the distinct molecular structures of the lipid A domains of the endotoxins derived from the three bacteria. Overall, we conclude that the combination of liquid crystal droplets and EndoNet provides the basis of a promising analytical approach for endotoxins that does not require use of complex biologically-derived reagents (e.g., Limulus amoebocyte lysate).

Application of lectin-based biosensor technology in the detection of foodborne pathogenic bacteria: a review

Foodborne diseases caused by pathogenic bacteria pose a serious threat to human health.

Enhanced antibacterial activity of the gentamicin against multidrug-resistant strains when complexed with Canavalia ensiformis lectin

The lectins are carbohydrate-binding proteins that are highly specific to sugar groups associated to other molecules. In addition to interacting with carbohydrates, a number of studies have reported the ability of these proteins to modulate the activity of several antibiotics against multidrug-resistant (MDR) strains. In this study, we report the enhanced antibacterial activity of the gentamicin against MDR strains when complexed with a lectin from Canavalia ensiformis seeds (ConA). Hemagglutination activity test and intrinsic fluorescence spectroscopy revealed that the gentamicin can interact with ConA most likely via the carbohydrate recognition domain (CRD) with binding constant (K_b) value estimated of (0.44 ± 0.04) x 10⁴ M^-1. Furthermore, the minimum inhibitory concentrations (MIC) obtained for ConA against all strains studied were not clinically relevant (MIC ≥ 1024 μg/mL). However, when ConA was combined with gentamicin, a significant increase in antibiotic activity was observed against Staphylococcus aureus and Escherichia coli. The present study showed that ConA has an affinity for gentamicin and modulates its activity against MDR strains. These results indicate that ConA improves gentamicin performance and is a promising candidate for structure/function analyses.

Chitosan Stabilized Silver Nanoparticles for the Electrochemical Detection of Lipopolysaccharide: A Facile Biosensing Approach for Gram-Negative Bacteria

Negatively charged lipopolysaccharide (LPS), a major endotoxin and component of the outer membrane of several Gram-negative bacteria, provides a useful biomarker for the indirect detection of these pathogens. For instance, Escherichia coli (E. coli) is a pathogenic bacterium that causes infections in almost all age groups, and has been implicated in food and water contamination. Current diagnostic and detection methods tend to be labor-intensive or expensive, necessitating the need for an easy, sensitive, rapid, and low-cost method. We report on the synthesis and use of positively charged chitosan stabilized silver nanoparticles (Chi-AgNPs) as a sensitive electrochemical nanobiosensor for the detection of LPS. Chi-AgNPs were synthesized through a facile, single step protocol, and characterized for size, charge, and morphology. Glassy carbon electrodes modified with Chi-AgNPs resulted in an enhancement of signal in the presence of both LPS and E. coli. Detection was accomplished over a large concentration range (several orders of magnitude) of 0.001–100 ng/mL and 10–10⁷ CFU/mL. The biosensors can reliably detect LPS and E. coli at very low concentrations. Chi-AgNPs have potential as low cost, sensitive nanobiosensors for Gram-negative bacteria due to strong electrostatic interaction with LPS present in their outer membranes.

Use of bacterial cellulose film modified by polypyrrole/TiO2-Ag nanocomposite for detecting and measuring the growth of pathogenic bacteria

The aim of this study was to use of bacterial cellulose/polypyrrole/TiO₂-Ag (BC/PPy/TiO₂-Ag) nanocomposite film to detect and measure the growth of 5 pathogenic bacteria. For this purpose, at first, 13 BC/PPy/TiO₂-Ag films were fabricated, then bacterial suspensions were prepared according to McFarland standard. The results showed that by increasing the bacterial concentration, the electrical resistance of sensors was decreased and there was a relation between bacterial concentration and bacterial type with electrical resistance change of sensors. The obtained data showed that the sensitivity of the sensors was increased with increasing the concentration of polypyrrole and TiO₂-Ag. FT-IR and SEM tests were performed to investigate the interaction between nanoparticles and determine the size of nanoparticles. The BC/PPy/TiO₂-Ag biosensors are portable and the response time of these sensors is very short for target analysis. Therefore, these sensors have the potential to improve biological safety as diagnostic tools.

Two-Step Isolation, Purification, and Characterization of Lectin from Zihua Snap Bean (Phaseolus vulgaris) Seeds

A two-step method based on an aqueous two-phase system and Sephadex G-75 was used to separate and purify lectin from the seeds of the Zihua snap bean. The preliminary properties and bioactivity of the Zihua snap bean lectin were characterized by different instrumental methods, such as sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS–PAGE), liquid chromatography-nano electrospray ionization mass spectrometry (Nano LC-ESI-MS/MS), and Fourier transform infrared spectroscopy (FTIR). The hemagglutinating activity of the Zihua snap bean lectin could not be inhibited by glucose, N-acetyl-d-glucosamine, d-galactose, N-acetyl-d-galactosamine, fructose, sucrose, d-maltose, d-trehalose, and lactose. It was found that the hemagglutinating activity of the lectin showed strong dependence on Mn²⁺ and Ca²⁺. The thermal and pH stability of the Zihua snap bean lectin was studied by FTIR and fluorescence spectroscopy. Relatively good stability was observed when the temperature was not higher than 70 °C, as well as in the pH range of 2.0 to 10.0. Digestive stability in vitro was investigated. The untreated lectin was relatively stable to pepsin and trypsin activity, but heat treatment could significantly reduce the digestive stability in vitro. Moreover, the lectin showed an inhibitory effect on the tested bacteria (Staphylococcus aureus (S. aureus), Escherichia coli (E. coli), Bacillus subtilis (B. subtilis)), and it also showed a certain inhibitory effect on the growth of Phytophthora infestans (P. infestans) at higher concentrations.

Antimicrobial Peptides: Powerful Biorecognition Elements to Detect Bacteria in Biosensing Technologies

Bacterial infections represent a serious threat in modern medicine. In particular, biofilm treatment in clinical settings is challenging, as biofilms are very resistant to conventional antibiotic therapy and may spread infecting other tissues. To address this problem, biosensing technologies are emerging as a powerful solution to detect and identify bacterial pathogens at the very early stages of the infection, thus allowing rapid and effective treatments before biofilms are formed. Biosensors typically consist of two main parts, a biorecognition moiety that interacts with the target (i.e., bacteria) and a platform that transduces such interaction into a measurable signal. This review will focus on the development of impedimetric biosensors using antimicrobial peptides (AMPs) as biorecognition elements. AMPs belong to the innate immune system of living organisms and are very effective in interacting with bacterial membranes. They offer unique advantages compared to other classical bioreceptor molecules such as enzymes or antibodies. Moreover, impedance-based sensors allow the development of label-free, rapid, sensitive, specific and cost-effective sensing platforms. In summary, AMPs and impedimetric transducers combine excellent properties to produce robust biosensors for the early detection of bacterial infections.

Separation and Enrichment of Lectin from Zihua Snap-Bean (Phaseolus vulgaris) Seeds by PEG 600-Ammonium Sulfate Aqueous Two-Phase System

A fast and efficient method based on a polyethylene glycol (PEG) 600/(NH₄)₂SO₄ aqueous two-phase system for extracting lectin from Zihua snap-bean (Phaseolus vulgaris) seeds was established. According to a Box-Behnken design (BBD), involving four factors at three levels each subjected to analysis of variance (ANOVA) and response surface analysis, the protein recovery and the purification factor of lectin in the top phase were used as the response values of the variance analysis to acquire the multivariate quadratic regression model. SDS-PAGE electrophoresis and the hemagglutination test were used to detect the distribution of lectin in the aqueous two-phase system (ATPS). The obtained data indicated that lectin was preferentially partitioned into the PEG-rich phase, and the ATPS, composed of 15% (NH₄)₂SO₄ (w/w), 18% PEG 600 (w/w), 0.4 g/5 g NaCl and 1 mL crude extract, showed good selectivity for lectin when the pH value was 7.5. Under the optimal conditions, most of the lectin was assigned to the top phase in the ATPS, and the hemagglutination activity of the purified lectin in the top phase was 3.08 times that of the crude extract. Consequently, the PEG 600/(NH₄)₂SO₄ aqueous two-phase system was an effective method for separating and enriching lectin directly from the crude extract of Zihua snap-bean seeds.

Ultrasensitive electrochemical detection of tumor cells based on multiple layer CdS quantum dots-functionalized polystyrene microspheres and graphene oxide - polyaniline composite

In this work, a novel ultrasensitive electrochemical biosensor was developed for the detection of K562 cell by a signal amplification strategy based on multiple layer CdS QDs functionalized polystyrene microspheres(PS) as bioprobe and graphene oxide(GO) -polyaniline(PANI) composite as modified materials of capture electrode. Due to electrostatic force of different charge, CdS QDs were decorated on the surface of PS by PDDA (poly(diallyldimethyl-ammonium chloride)) through a layer-by-layer(LBL) assemble technology, in which the structure of multiple layer CdS QDs increased the detection signal intensity. Moreover, GO-PANI composite not only enhanced the electron transfer rate, but also increased tumor cells load ratio. The resulting electrochemical biosensor was used to detect K562 cells with a lower detection limit of 3 cellsmL^-1 (S/N = 3) and a wider linear range from 10 to 1.0 × 10⁷ cellsmL^-1. This sensor was also used for mannosyl groups on HeLa cells and Hct116 cells, which showed high specificity and sensitivity. This signal amplification strategy would provide a novel approach for detection, diagnosis and treatment for tumor cells.

Recent Progress in Lectin-Based Biosensors

This article reviews recent progress in the development of lectin-based biosensors used for the determination of glucose, pathogenic bacteria and toxins, cancer cells, and lectins. Lectin proteins have been widely used for the construction of optical and electrochemical biosensors by exploiting the specific binding affinity to carbohydrates. Among lectin proteins, concanavalin A (Con A) is most frequently used for this purpose as glucose- and mannose-selective lectin. Con A is useful for immobilizing enzymes including glucose oxidase (GOx) and horseradish peroxidase (HRP) on the surface of a solid support to construct glucose and hydrogen peroxide sensors, because these enzymes are covered with intrinsic hydrocarbon chains. Con A-modified electrodes can be used as biosensors sensitive to glucose, cancer cells, and pathogenic bacteria covered with hydrocarbon chains. The target substrates are selectively adsorbed to the surface of Con A-modified electrodes through strong affinity of Con A to hydrocarbon chains. A recent topic in the development of lectin-based biosensors is a successful use of nanomaterials, such as metal nanoparticles and carbon nanotubes, for amplifying output signals of the sensors. In addition, lectin-based biosensors are useful for studying glycan expression on living cells.

Biophysical characterization of lectin–glycan interactions for therapeutics, vaccines and targeted drug-delivery

Lectin–glycan interactions play a role in biological processes, host–pathogen interactions and in disease. A more detailed understanding of these interactions is not only useful for the elucidation of their biological function but can also be applied in immunology, drug development and delivery and diagnostics. We review some commonly used biophysical techniques for studying lectin–glycan interactions; namely: frontal affinity chromatography, glycan/lectin microarray, surface plasmon resonance, electrochemical impedance spectroscopy, isothermal titration calorimetry, fluorescent assays, enzyme linked lectin sorbent assay and saturation transfer difference nuclear magnetic resonance spectroscopy. Each method is evaluated on efficiency, cost and throughput. We also consider the advantages and limitations of each technique and provide examples of their application in biology, drug discovery and delivery, immunology, glycoprofiling and biosensing.