Impedance sensing and molecular modeling of an olfactory biosensor based on chemosensory proteins of honeybee

Key residues involved in the interaction between chlorpyrifos and a chemosensory protein in Rhopalosiphum padi: Implication for tracking chemical residues via insect olfactory proteins

The development of advanced biosensors for tracking chemical residues and detecting environmental pollution is of great significance. Insect chemical sensory proteins, including chemosensory proteins (CSPs), are easy to synthesize and purify and have been used to design proteins for specific biosensor applications. Chlorpyrifos is one of the most commonly used chemicals for controlling insect pests in agriculture. This organophosphate is harmful to aquatic species and has long-term negative consequences for the ecosystem. CSPs can bind and carry a variety of environmental chemicals, including insecticides. However, the mechanism by which CSPs bind to insecticides in aphids has not been clarified. In this study, we discovered that RpCSP1 from Rhopalosiphum padi has a higher affinity for chlorpyrifos, with a Ki value of 4.763 ± 0.491 μM. Multispectral analysis revealed the physicochemical binding mechanism between RpCSP1 and chlorpyrifos. Computational simulation analysis demonstrated that the main factor promoting the development of the RpCSP1-chlorpyrifos complex is polar solvation energy. Four residues (Arg33, Glu94, Gln145, Lys153) were essential in facilitating the interaction between RpCSP1 and chlorpyrifos. Our research has improved knowledge of the relationship between CSPs and organophosphorus pesticides. This knowledge contributes to the advancement of biosensor chips for tracking chemical residues and detecting environmental pollution through the use of CSPs.

High-efficiency removal of pyrethroids using a redesigned odorant binding protein

Pyrethroids are ubiquitously present in environmental media and threaten both the ecosystem and human health. To explore effective ways to remove pyrethroids from the environment, an odorant binding protein (OBP) with affinity for various pyrethroids was investigated. Initially, the target OBP, Spodoptera littoralis pheromone binding protein 1 (SlitPBP1), underwent redesign to enhance its affinity for pyrethroids. The modified SlitPBP1E97ND106E demonstrated a substantially increased affinity for deltamethrin (DeltaM), with a dissociation constant of 0.77 ± 0.17 μM. The affinity of SlitPBP1E97ND106E for other pyrethroids also increased to varying extents. Consequently, SlitPBP1E97ND106E displayed a markedly enhanced capability to adsorb and remove pyrethroids. When exposed to free SlitPBP1E97ND106E in solution, the reduction in DeltaM surged from 16.78 ± 0.32% to 97.51 ± 0.56%. SlitPBP1E97ND106E was immobilized by coupling the protein to Ni2+-NTA agarose resin. Liquid chromatography results attested to the superior efficacy of immobilized SlitPBP1E97ND106E in removing pyrethroids, especially DeltaM. No significant differences in pyrethroid removal were detected across various water samples. Our findings introduce a potent tool for pyrethroid removal. A wider range of OBPs can similarly be optimized and applied to remove organic pollutants, including but not limited to pesticides.

An Overview of Artificial Olfaction Systems with a Focus on Surface Plasmon Resonance for the Analysis of Volatile Organic Compounds

The last three decades have witnessed an increasing demand for novel analytical tools for the analysis of gases including odorants and volatile organic compounds (VOCs) in various domains. Traditional techniques such as gas chromatography coupled with mass spectrometry, although very efficient, present several drawbacks. Such a context has incited the research and industrial communities to work on the development of alternative technologies such as artificial olfaction systems, including gas sensors, olfactory biosensors and electronic noses (eNs). A wide variety of these systems have been designed using chemiresistive, electrochemical, acoustic or optical transducers. Among optical transduction systems, surface plasmon resonance (SPR) has been extensively studied thanks to its attractive features (high sensitivity, label free, real-time measurements). In this paper, we present an overview of the advances in the development of artificial olfaction systems with a focus on their development based on propagating SPR with different coupling configurations, including prism coupler, wave guide, and grating.

Graphene Bioelectronic Nose for the Detection of Odorants with Human Olfactory Receptor 2AG1

A real-time sensor for the detection of amyl butyrate (AB) utilising human olfactory receptor 2AG1 (OR2AG1), a G-protein coupled receptor (GPCR) consisting of seven transmembrane domains, immobilized onto a graphene resistor is demonstrated. Using CVD graphene as the sensor platform, allows greater potential for more sensitive detection than similar sensors based on carbon nanotubes, gold or graphene oxide platforms. A specific graphene resistor sensor was fabricated and modified via non-covalent π–π stacking of 1,5 diaminonaphthalene (DAN) onto the graphene channel, and subsequent anchoring of the OR2AG1 receptor to the DAN molecule using glutaraldehyde coupling. Binding between the target odorant, amyl butyrate, and the OR2AG1 receptor protein generated a change in resistance of the graphene resistor sensor. The functionalized graphene resistor sensors exhibited a linear sensor response between 0.1–500 pM and high selectively towards amyl butyrate, with a sensitivity as low as 500 fM, whilst control measurements using non-specific esters, produced a negligible sensor response. The approach described here provides an alternative sensing platform that can be used in bioelectronic nose applications.

Molecularly Imprinted Polyscopoletin for the Electrochemical Detection of the Chronic Disease Marker Lysozyme

Herein we report the electropolymerization of a scopoletin based molecularly imprinted polymer (MIP) for the detection of lysozyme (Lyz), an enzymatic marker of several diseases in mammalian species. Two different approaches have been used for the imprinting of lysozyme based, respectively, on the use of a monomer-template mixture and on the covalent immobilization of the enzyme prior to polymer synthesis. In the latter case, a multi-step protocol has been exploited with preliminary functionalization of gold electrode with amino groups, via 4-aminothiophenol, followed by reaction with glutaraldehyde, to provide a suitable linker for lysozyme. Each step of surface electrode modification has been followed by cyclic voltammetry and electrochemical impedance spectroscopy, which has been also employed to test the electrochemical responses of the developed MIP. The sensors show good selectivity to Lyz and detect the enzyme at concentrations up to 292 mg/L (20 μM), but with different performances, depending on the used imprinting approach. An imprinting factor equal to 7.1 and 2.5 and a limit of detection of 0.9 mg/L (62 nM) and 2.1 mg/L (141 nM) have been estimated for MIPs prepared with and without enzyme immobilization, respectively. Competitive rebinding experiment results show that this sensing material is selective for Lyz determination. Tests were performed using synthetic saliva to evaluate the potential application of the sensors in real matrices for clinical purposes.

Recent advances in computational methods for biosensor design

Biosensors are analytical tools with a great application in healthcare, food quality control, and environmental monitoring. They are of considerable interest to be designed by using cost-effective and efficient approaches. Designing biosensors with improved functionality or application in new target detection has been converted to a fast-growing field of biomedicine and biotechnology branches. Experimental efforts have led to valuable successes in the field of biosensor design; however, some deficiencies restrict their utilization for this purpose. Computational design of biosensors is introduced as a promising key to eliminate the gap. A set of reliable structure prediction of the biosensor segments, their stability, and accurate descriptors of molecular interactions are required to computationally design biosensors. In this review, we provide a comprehensive insight into the progress of computational methods to guide the design and development of biosensors, including molecular dynamics simulation, quantum mechanics calculations, molecular docking, virtual screening, and a combination of them as the hybrid methodologies. By relying on the recent advances in the computational methods, an opportunity emerged for them to be complementary or an alternative to the experimental methods in the field of biosensor design.

Current and potential biotechnological applications of odorant-binding proteins

Odorant-binding proteins (OBPs) are small soluble proteins whose biological function is believed to be facilitating olfaction by assisting the transport of volatile chemicals in both vertebrate and insect sensory organs, where they are secreted. Their capability to interact with a broad range of hydrophobic compounds combined with interesting features such as being small, stable, and easy to produce and modify, makes them suitable targets for applied research in various industrial segments, including textile, cosmetic, pesticide, and pharmaceutical, as well as for military, environmental, health, and security field applications. In addition to reviewing already established biotechnological applications of OBPs, this paper also discusses their potential use in prospecting of new technologies. The development of new products for insect population management is currently the most prevailing use for OBPs, followed by biosensor technology, an area that has recently seen a significant increase in studies evaluating their incorporation into sensing devices. Finally, less typical approaches include applications in anchorage systems and analytical tools. KEY POINTS: • Odorant-binding proteins (OBPs) present desired characteristics for applied research. • OBPs are mainly used for developing new products for insect population control. • Incorporation of OBPs into chemosensory devices is a growing area of study. • Less conventional uses for OBPs include anchorage systems and analytical purposes. Graphical Abstract.

Electrochemical biosensing with odorant binding proteins

The development of sensors that mimic the natural smell sensing mechanism and selectively recognizes the odorants remains highly challenging. Electrochemical based sensing approaches aiming at monitoring molecular recognition events between surface receptors and analytes in solution or in the gas phase, are one possible transduction platforms among others for the construction of an artificial nose. The principle of electrochemical detection lies on the shift of the potential/current during the recognition event, which is proportional to the concentration of the analyte, in our case the odorant. A tremendous amount of efforts has been put into making electrochemical sensors sensitive and selective to the analyte of interest through the use of nanomaterials, development of different detection schemes and application of innovative receptor ligands for selective detection of the analyte. There have been significant advances in electrochemical based odorant sensing by using odorant binding proteins (OBP) as surface receptors, small soluble proteins present in nasal mucus at millimolar concentrations where the hydrophobic binding pocket gives the ability to reversibly bind odorant molecules. As OBPs are robust and easy to produce receptors, they are good candidates for the design of biosensors. In this chapter, we focus on the progress made on the detection of odorant molecules using OBPs as a bioreceptor and electrochemistry as a transduction method.

Tools in the Investigation of Volatile Semiochemicals on Insects: From Sampling to Statistical Analysis

The recognition of volatile organic compounds (VOCs) involved in insect interactions with plants or other organisms is essential for constructing a holistic comprehension of their role in ecology, from which the implementation of new strategies for pest and disease vector control as well as the systematic exploitation of pollinators and natural enemies can be developed. In the present paper, some of the general methods employed in this field are examined, focusing on their available technologies. An important part of the investigations conducted in this context begin with VOC collection directly from host organisms, using classical extraction methods, by the employment of adsorption materials used in solid-phase micro extraction (SPME) and direct-contact sorptive extraction (DCSE) and, subsequently, analysis through instrumental analysis techniques such as gas chromatography (GC), nuclear magnetic resonance (NMR) and mass spectrometry (MS), which provide crucial information for determining the chemical identity of volatile metabolites. Behavioral experiments, electroantennography (EAG), and biosensors are then carried out to define the semiochemicals with the best potential for performing relevant functions in ecological relationships. Chemical synthesis of biologically-active VOCs is alternatively performed to scale up the amount to be used in different purposes such as laboratory or field evaluations. Finally, the application of statistical analysis provides tools for drawing conclusions about the type of correlations existing between the diverse experimental variables and data matrices, thus generating models that simplify the interpretation of the biological roles of VOCs.

Functional Analysis of the Chemosensory Protein GmolCSP8 From the Oriental Fruit Moth, Grapholita molesta (Busck) (Lepidoptera: Tortricidae)

Chemosensory proteins (CSPs) belong to a family of small water-soluble proteins that can selectively bind and transport odorant molecules for olfactory communication in insects. To date, their definite physiological functions in olfaction remain controversial when compared with odorant binding proteins (OBPs). To investigate the functions of CSPs in the oriental fruit moth Grapholita molesta, we determined the tissue expression patterns and binding properties of the CSP, GmolCSP8. The key binding sites of GmolCSP8 with a representative ligand were evaluated using molecular flexible docking, site-directed mutagenesis and ligand-binding experiments. Multiple sequence alignment and phylogenetic analysis showed that GmolCSP8 possesses a typical conserved four cysteines motif and shares high sequence identity with some CSP members of other Lepidopteran insects. GmolCSP8 was predominantly expressed in the wings and antennae of both male and female adults and may be involve in contact chemoreception. Recombinant GmolCSP8 (rGmolCSP8) exhibited specific-binding affinities to small aliphatic alcohols (C4–12) and had the strongest binding affinity to 1-hexanol. The three-dimensional structure of GmolCSP8 was constructed using the structure of sgCSP4 as a template. Site-directed mutagenesis and ligand-binding experiments confirmed that Thr27 is the key binding site in GmolCSP8 for 1-hexanol binding, because this residue can form hydrogen bond with the oxygen atom of the hydroxyl group in 1-hexanol, and Leu30 may play an important role in binding to 1-hexanol. We found that pH significantly affected the binding affinities of rGmolCSP8 to ligand, revealing that ligand-binding and -release by this protein is related to a pH-dependent conformational transition. Based on these results, we infer that GmolCSP8 may participate in the recognition and transportation of 1-hexanol and other small aliphatic alcohols.

Odorant-Binding Proteins as Sensing Elements for Odour Monitoring

Odour perception has been the object of fast growing research interest in the last three decades. Parallel to the study of the corresponding biological systems, attempts are being made to model the olfactory system with electronic devices. Such projects range from the fabrication of individual sensors, tuned to specific chemicals of interest, to the design of multipurpose smell detectors using arrays of sensors assembled in a sort of artificial nose. Recently, proteins have attracted increasing interest as sensing elements. In particular, soluble olfaction proteins, including odorant-binding proteins (OBPs) of vertebrates and insects, chemosensory proteins (CSPs) and Niemann-Pick type C2 (NPC2) proteins possess interesting characteristics for their use in sensing devices for odours. In fact, thanks to their compact structure, their soluble nature and small size, they are extremely stable to high temperature, refractory to proteolysis and resistant to organic solvents. Moreover, thanks to the availability of many structures solved both as apo-proteins and in complexes with some ligands, it is feasible to design mutants by replacing residues in the binding sites with the aim of synthesising proteins with better selectivity and improved physical properties, as demonstrated in a number of cases.

From Gas Sensors to Biomimetic Artificial Noses

Since the first attempts to mimic the human nose with artificial devices, a variety of sensors have been developed, ranging from simple inorganic and organic gas detectors to biosensing elements incorporating proteins of the biological olfactory system. In order to design a device able to mimic the human nose, two major issues still need to be addressed regarding the complexity of olfactory coding and the extreme sensitivity of the biological system. So far, only 50 of the approximately 300–400 functioning olfactory receptors have been de-orphanized, still a long way from breaking the human olfactory code. On the other hand, the exceptional sensitivity of the human nose is based on amplification mechanisms difficult to reproduce with electronic circuits, and perhaps novel approaches are required to address this issue. Here, we review the recent literature on chemical sensing both in biological systems and artificial devices, and try to establish the state-of-the-art towards the design of an electronic nose.

From radioactive ligands to biosensors: binding methods with olfactory proteins

In this paper, we critically review the binding protocols currently reported in the literature to measure the affinity of odorants and pheromones to soluble olfactory proteins, such as odorant-binding proteins (OBPs), chemosensory proteins (CSPs) and Niemann-Pick class C2 (NPC2) proteins. The first part contains a brief introduction on the principles of binding and a comparison of the techniques adopted or proposed so far, discussing advantages and problems of each technique, as well as their suitable application to soluble olfactory proteins. In the second part, we focus on the fluorescent binding assay, currently the most widely used approach. We analyse advantages and drawbacks, trying to identify the causes of anomalous behaviours that have been occasionally observed, and suggest how to interpret the experimental data when such events occur. In the last part, we describe the state of the art of biosensors for odorants, using soluble olfactory proteins immobilised on biochips, and discuss the possibility of using such approach as an alternative way to measure binding events and dissociation constants.

An overview of an artificial nose system

The present review describes recent advances in the development of an artificial nose system based on olfactory receptors and various sensing platforms. The kind of artificial nose, the production of olfactory receptors, the sensor platform for signal conversion and the application of the artificial nose system based on olfactory receptors and various sensing platforms are presented. The associated transduction modes are also discussed. The paper presents a review of the latest achievements and a critical evaluation of the state of the art in the field of artificial nose systems.

Post hoc support vector machine learning for impedimetric biosensors based on weak protein–ligand interactions

We develop a simple, open source machine learning algorithm for analyzing impedimetric biosensor data using a mobile phone.

Identification of Candidate Odorant-Binding Protein and Chemosensory Protein Genes in Cyrtorhinus lividipennis (Hemiptera: Miridae), a Key Predator of the Rice Planthoppers in Asia

Cyrtorhinus lividipennis Reuter (Hemiptera: Miridae) is an important predatory natural enemy of planthopper and leafhopper eggs in Asian rice paddy fields. Cyrtorhinus lividipennis is known to rely largely on herbivore-induced plant volatiles to identify eggs embedded in rice stem tissues for feeding and on pheromones for mating. However, exactly how C. lividipennis decode these chemical information is unclear. In most insects, the odorant-binding proteins (OBPs) and the chemosensory proteins (CSPs) are essential for seeking out food resources and mates. In this study, we identified 10 OBP and 5 CSP genes in C. lividipennis and investigated their expression patterns in various tissues of adult males and females by quantitative real-time PCR (qRT-PCR). Six OBP genes (ClivOBP1, 2, 4, 6, 9, and 10) were mainly expressed in the male antennae, whereas three genes (ClivOBP3, ClivOBP7, and ClivOBP8) had high expression in the female antennae. ClivCSP1 was predominantly expressed in the male antennae. These findings suggest that most ClivOBPs and ClivCSPs are likely involved in food-searching behavior. The recognition of the pheromone molecules provides the basis for further functional studies on the chemoreception system of C. lividipennis.

Identification of Chinese Herbal Medicines with Electronic Nose Technology: Applications and Challenges

This paper provides a review of the most recent works in machine olfaction as applied to the identification of Chinese Herbal Medicines (CHMs). Due to the wide variety of CHMs, the complexity of growing sources and the diverse specifications of herb components, the quality control of CHMs is a challenging issue. Much research has demonstrated that an electronic nose (E-nose) as an advanced machine olfaction system, can overcome this challenge through identification of the complex odors of CHMs. E-nose technology, with better usability, high sensitivity, real-time detection and non-destructive features has shown better performance in comparison with other analytical techniques such as gas chromatography-mass spectrometry (GC-MS). Although there has been immense development of E-nose techniques in other applications, there are limited reports on the application of E-noses for the quality control of CHMs. The aim of current study is to review practical implementation and advantages of E-noses for robust and effective odor identification of CHMs. It covers the use of E-nose technology to study the effects of growing regions, identification methods, production procedures and storage time on CHMs. Moreover, the challenges and applications of E-nose for CHM identification are investigated. Based on the advancement in E-nose technology, odor may become a new quantitative index for quality control of CHMs and drug discovery. It was also found that more research could be done in the area of odor standardization and odor reproduction for remote sensing.

A Novel Semi-Supervised Method of Electronic Nose for Indoor Pollution Detection Trained by M-S4VMs

Electronic nose (E-nose), as a device intended to detect odors or flavors, has been widely used in many fields. Many labeled samples are needed to gain an ideal E-nose classification model. However, the labeled samples are not easy to obtain and there are some cases where the gas samples in the real world are complex and unlabeled. As a result, it is necessary to make an E-nose that cannot only classify unlabeled samples, but also use these samples to modify its classification model. In this paper, we first introduce a semi-supervised learning algorithm called S4VMs and improve its use within a multi-classification algorithm to classify the samples for an E-nose. Then, we enhance its performance by adding the unlabeled samples that it has classified to modify its model and by using an optimization algorithm called quantum-behaved particle swarm optimization (QPSO) to find the optimal parameters for classification. The results of comparing this with other semi-supervised learning algorithms show that our multi-classification algorithm performs well in the classification system of an E-nose after learning from unlabeled samples.

A Novel Optimization Technique to Improve Gas Recognition by Electronic Noses Based on the Enhanced Krill Herd Algorithm

An electronic nose (E-nose) is an intelligent system that we will use in this paper to distinguish three indoor pollutant gases (benzene (C₆H₆), toluene (C₇H₈), formaldehyde (CH₂O)) and carbon monoxide (CO). The algorithm is a key part of an E-nose system mainly composed of data processing and pattern recognition. In this paper, we employ support vector machine (SVM) to distinguish indoor pollutant gases and two of its parameters need to be optimized, so in order to improve the performance of SVM, in other words, to get a higher gas recognition rate, an effective enhanced krill herd algorithm (EKH) based on a novel decision weighting factor computing method is proposed to optimize the two SVM parameters. Krill herd (KH) is an effective method in practice, however, on occasion, it cannot avoid the influence of some local best solutions so it cannot always find the global optimization value. In addition its search ability relies fully on randomness, so it cannot always converge rapidly. To address these issues we propose an enhanced KH (EKH) to improve the global searching and convergence speed performance of KH. To obtain a more accurate model of the krill behavior, an updated crossover operator is added to the approach. We can guarantee the krill group are diversiform at the early stage of iterations, and have a good performance in local searching ability at the later stage of iterations. The recognition results of EKH are compared with those of other optimization algorithms (including KH, chaotic KH (CKH), quantum-behaved particle swarm optimization (QPSO), particle swarm optimization (PSO) and genetic algorithm (GA)), and we can find that EKH is better than the other considered methods. The research results verify that EKH not only significantly improves the performance of our E-nose system, but also provides a good beginning and theoretical basis for further study about other improved krill algorithms’ applications in all E-nose application areas.

A Novel Semi-Supervised Electronic Nose Learning Technique: M-Training

When an electronic nose (E-nose) is used to distinguish different kinds of gases, the label information of the target gas could be lost due to some fault of the operators or some other reason, although this is not expected. Another fact is that the cost of getting the labeled samples is usually higher than for unlabeled ones. In most cases, the classification accuracy of an E-nose trained using labeled samples is higher than that of the E-nose trained by unlabeled ones, so gases without label information should not be used to train an E-nose, however, this wastes resources and can even delay the progress of research. In this work a novel multi-class semi-supervised learning technique called M-training is proposed to train E-noses with both labeled and unlabeled samples. We employ M-training to train the E-nose which is used to distinguish three indoor pollutant gases (benzene, toluene and formaldehyde). Data processing results prove that the classification accuracy of E-nose trained by semi-supervised techniques (tri-training and M-training) is higher than that of an E-nose trained only with labeled samples, and the performance of M-training is better than that of tri-training because more base classifiers can be employed by M-training.

Ligands binding and molecular simulation: the potential investigation of a biosensor based on an insect odorant binding protein

Based on mimicking biological olfaction, biosensors have been applied for the detection of various ligands in complex environment, which could represent one of the most promising research fields. In this study, the basic characters of one insect odorant binding protein (OBP) as a biosensor were explored. To explore the molecular recognition process, the tertiary structure of the protein was modeled and the protein-ligand interactions with 1,536,550 chemicals were investigated by the molecular docking. The availability of large amount of recombinant SlitOBP1 overcame the difficulty to obtain biological sensing material. After obtained the purified recombinant protein, the result of fluorescence binding assays proved the candidate protein has good affinities with the majority of the tested chemicals. With the aid of simulation docking, the key conserved amino acids within the binding site were identified and then mutated to alanine. After mutation, the protein-ligand binding characteristics were recorded, and the competitive binding assays were carried out to provide experimental verification. The detailed information on its structure and affinities investigated in this study could allow the design of specific mutants with desired characteristics, which provides a solid base for tailoring OBP for biosensor and provides a role model for screening the other elements in olfactory system for different applications.

Structure and biotechnological applications of odorant-binding proteins

Odorant-binding proteins (OBPs) are small soluble polypeptides found in sensory organs of vertebrates and insects as well as in secretory glands and are dedicated to detection and release of chemical stimuli. OBPs of vertebrates belong to the family of lipocalin proteins, while those of insects are folded into α-helical domains. Both types of architectures are extremely stable to temperature, organic solvents and proteolytic digestion. These characteristics make OBPs suitable elements for fabricating biosensors to be used in the environment, as well as for other biotechnological applications. The affinity of OBPs for small volatile organic compounds is in the micromolar range, and they have broad specificity to a range of ligands. For biotechnological applications, OBPs can be expressed in bacterial systems at low cost and are easily purified. The large amount of information available on their structures and affinities to different molecules should allow the design of specific mutants with desired characteristics and represent a solid base for tailoring OBPs for different applications.