The progress of olfactory transduction and biomimetic olfactory-based biosensors

Olfactory biosensor for smart agriculture

The high-quality development of agriculture is related to the survival of human beings. Olfactory biosensors show great potential for application in agriculture with their significant advantages in sensitivity, selectivity, and stability. This paper reviews the development history of olfactory biosensors, introduces the characteristics of their sensitive layer, analyzes the signal conversion mechanism, describes the preparation techniques, and discusses the application of olfactory biosensors in agriculture. The current application challenges, future trends, and economics of olfactory biosensors are also analyzed. Hopefully, this paper will provide a new perspective for the research of olfactory biosensors in agriculture, promote the further development of related technologies, and support the realization of smart agriculture and green transformation of agriculture.

Flexible analysis of spatial transcriptomics data (FAST): a deconvolution approach

MOTIVATION

Spatial transcriptomics is a state-of-art technique that allows researchers to study gene expression patterns in tissues over the spatial domain. As a result of technical limitations, the majority of spatial transcriptomics techniques provide bulk data for each sequencing spot. Consequently, in order to obtain high-resolution spatial transcriptomics data, performing deconvolution becomes essential. Most existing deconvolution methods rely on reference data (e.g., single-cell data), which may not be available in real applications. Current reference-free methods encounter limitations due to their dependence on distribution assumptions, reliance on marker genes, or the absence of leveraging histology and spatial information. Consequently, there is a critical need for the development of highly flexible, robust, and user-friendly reference-free deconvolution methods capable of unifying or leveraging case-specific information in the analysis of spatial transcriptomics data.

RESULTS

We propose a novel reference-free method based on regularized non-negative matrix factorization (NMF), named Flexible Analysis of Spatial Transcriptomics (FAST), that can effectively incorporate gene expression data, spatial, and histology information into a unified deconvolution framework. Compared to existing methods, FAST imposes fewer distribution assumptions, utilizes the spatial structure information of tissues, and encourages interpretable factorization results. These features enable greater flexibility and accuracy, making FAST an effective tool for deciphering the complex cell-type composition of tissues and advancing our understanding of various biological processes and diseases. Extensive simulation studies have shown that FAST outperforms other existing reference-free methods. In real data applications, FAST is able to uncover the underlying tissue structures and identify the corresponding marker genes.

Field-Effect Sensors Using Biomaterials for Chemical Sensing

After millions of years of evolution, biological chemical sensing systems (i.e., olfactory and taste systems) have become very powerful natural systems which show extreme high performances in detecting and discriminating various chemical substances. Creating field-effect sensors using biomaterials that are able to detect specific target chemical substances with high sensitivity would have broad applications in many areas, ranging from biomedicine and environments to the food industry, but this has proved extremely challenging. Over decades of intense research, field-effect sensors using biomaterials for chemical sensing have achieved significant progress and have shown promising prospects and potential applications. This review will summarize the most recent advances in the development of field-effect sensors using biomaterials for chemical sensing with an emphasis on those using functional biomaterials as sensing elements such as olfactory and taste cells and receptors. Firstly, unique principles and approaches for the development of these field-effect sensors using biomaterials will be introduced. Then, the major types of field-effect sensors using biomaterials will be presented, which includes field-effect transistor (FET), light-addressable potentiometric sensor (LAPS), and capacitive electrolyte–insulator–semiconductor (EIS) sensors. Finally, the current limitations, main challenges and future trends of field-effect sensors using biomaterials for chemical sensing will be proposed and discussed.

Different Ways to Apply a Measurement Instrument of E-Nose Type to Evaluate Ambient Air Quality with Respect to Odour Nuisance in a Vicinity of Municipal Processing Plants

This review paper presents different ways to apply a measurement instrument of e-nose type to evaluate ambient air with respect to detection of the odorants characterized by unpleasant odour in a vicinity of municipal processing plants. An emphasis was put on the following applications of the electronic nose instruments: monitoring networks, remote controlled robots and drones as well as portable devices. Moreover, this paper presents commercially available sensors utilized in the electronic noses and characterized by the limit of quantification below 1 ppm v/v, which is close to the odour threshold of some odorants. Additionally, information about bioelectronic noses being a possible alternative to electronic noses and their principle of operation and application potential in the field of air evaluation with respect to detection of the odorants characterized by unpleasant odour was provided.

Biomimetic chemical sensors using bioengineered olfactory and taste cells

Biological olfactory and taste systems are natural chemical sensing systems with unique performances for the detection of environmental chemical signals. With the advances in olfactory and taste transduction mechanisms, biomimetic chemical sensors have achieved significant progress due to their promising prospects and potential applications. Biomimetic chemical sensors exploit the unique capability of biological functional components for chemical sensing, which are often sourced from sensing units of biological olfactory or taste systems at the tissue level, cellular level, or molecular level. Specifically, at the cellular level, there are mainly two categories of cells have been employed for the development of biomimetic chemical sensors, which are natural cells and bioengineered cells, respectively. Natural cells are directly isolated from biological olfactory and taste systems, which are convenient to achieve. However, natural cells often suffer from the undefined sensing properties and limited amount of identical cells. On the other hand, bioengineered cells have shown decisive advantages to be applied in the development of biomimetic chemical sensors due to the powerful biotechnology for the reconstruction of the cell sensing properties. Here, we briefly summarized the most recent advances of biomimetic chemical sensors using bioengineered olfactory and taste cells. The development challenges and future trends are discussed as well.

Study on Odor Source Localization Method Based on Bionic Olfaction

This paper proposes an odor source localization method based on bionic olfaction. The special nasal cavity and turnable head make mammalian have excellent odor source localization ability. According to this principle, a turnable bionic odor sensing device is proposed by this paper for odor source localization system. This sensing device can rotate freely within the range level 360°, and the detection directions of its sensing channels are different. This also proposes a pattern recognition algorithm based on K-L transform to analyze the data collected by odor sensing device, and the features of odor source are extracted correctly. Experimental results for odor source localization demonstrate the feasibility of the proposed approach.

Response enhancement of olfactory sensory neurons-based biosensors for odorant detection

This paper presents a novel strategy for the response enhancement of olfactory sensory neurons (OSNs)-based biosensors by monitoring the enhancive responses of OSNs to odorants. An OSNs-based biosensor was developed on the basis of the light addressable potentiometric sensor (LAPS), in which rat OSNs were cultured on the surface of LAPS chip and served as sensing elements. LY294002, the specific inhibitor of phosphatidylinositol 3-kinase (PI3K), was used to enhance the responses of OSNs to odorants. The responses of OSNs to odorants with and without the treatment of LY294002 were recorded by LAPS. The results show that the enhancive effect of LY294002 was recorded efficiently by LAPS and the responses of this OSNs-LAPS hybrid biosensor were enhanced by LY294002 by about 1.5-fold. We conclude that this method can enhance the responses of OSNs-LAPS hybrid biosensors, which may provide a novel strategy for the bioelectrical signal monitor of OSNs in biosensors. It is also suggested that this strategy may be applicable to other kinds of OSNs-based biosensors for cellular activity detection, such as microelectrode array (MEA) and field effect transistor (FET).