Electrophysiological evidence of RML12 mosquito cell line towards neuronal differentiation by 20-hydroxyecdysdone

Insect Cell-Based Models: Cell Line Establishment and Application in Insecticide Screening and Toxicology Research

During the past decades, research on insect cell culture has grown tremendously. Thousands of lines have been established from different species of insect orders, originating from several tissue sources. These cell lines have often been employed in insect science research. In particular, they have played important roles in pest management, where they have been used as tools to evaluate the activity and explore the toxic mechanisms of insecticide candidate compounds. This review intends to first briefly summarize the progression of insect cell line establishment. Then, several recent studies based on insect cell lines coupled with advanced technologies are introduced. These investigations revealed that insect cell lines can be exploited as novel models with unique advantages such as increased efficiency and reduced cost compared with traditional insecticide research. Most notably, the insect cell line-based models provide a global and in-depth perspective to study the toxicology mechanisms of insecticides. However, challenges and limitations still exist, especially in the connection between in vitro activity and in vivo effectiveness. Despite all this, recent advances have suggested that insect cell line-based models promote the progress and sensible application of insecticides, which benefits pest management.

Spontaneous Cell Cluster Formation in Human iPSC-Derived Neuronal Spheroid Networks Influences Network Activity

Three-dimensional neuronal culture systems such as spheroids, organoids, and assembloids constitute a branch of neuronal tissue engineering that has improved our ability to model the human brain in the laboratory. However, the more elaborate the brain model, the more difficult it becomes to study functional properties such as electrical activity at the neuronal level, similar to the challenges of studying neurophysiology in vivo We describe a simple approach to generate self-assembled three-dimensional neuronal spheroid networks with defined human cell composition on microelectrode arrays. Such spheroid networks develop a highly three-dimensional morphology with cell clusters up to 60 µm in thickness and are interconnected by pronounced bundles of neuronal fibers and glial processes. We could reliably record from up to hundreds of neurons simultaneously per culture for ≤90 d. By quantifying the formation of these three-dimensional structures over time, while regularly monitoring electrical activity, we were able to establish a strong link between spheroid morphology and network activity. In particular, the formation of cell clusters accelerates formation and maturation of correlated network activity. Astrocytes both influence electrophysiological network activity as well as accelerate the transition from single cell layers to cluster formation. Higher concentrations of astrocytes also have a strong effect of modulating synchronized network activity. This approach thus represents a practical alternative to often complex and heterogeneous organoids, providing easy access to activity within a brain-like 3D environment.Significance StatementNeuronal "organoid" cultures with multiple cell types grown on elaborate three-dimensional scaffolds have become popular tools to generate brain-like properties in vitro but bring with them similar problems concerning access to physiological function as real brain tissue. Here, we developed a new approach to form simple brain-like spheroid networks from human neurons, but using the normal supporting cells of the brain, astrocytes, as the scaffold. By growing these cultures on conventional microelectrode arrays, we were able to observe development of complex patterns of electrical activity for months. Our results highlight how formation of three-dimensional structures accelerated the formation of synchronized neuronal network activity and provide a promising new simple model system for studying interactions between known human cell types in vitro.

Chemical Treatments for Insect Cell Differentiation: The Effects of 20-Hydroxyecdysone and Veratridine on Cultured Spodoptera frugiperda (Sf21) Insect Cell Ultrastructure

Simple Summary

Cultured insect Sf21 cells treated with the hormone 20-hydroxyecdysone grow long processes and resemble neurons. They also make physical contact with one another and appear to have the potential to form synapses, areas in which nerve cells are in close contact and communicate with one another electrically or by the release of chemical transmitters. This study uses electron microscopy to look for structural evidence of synapses in 20-hydroxyexdysone treated Sf21 cell cultures. Unfortunately, no evidence of synaptic structures were observed, suggesting that other factors are required for the formation of functional synapses in these cultures.

Abstract

Previous studies have shown that insect cell cultures stop dividing, form clumps, and can be induced to grow processes reminiscent of axons, when the culture medium is supplemented with 20-hydroxyecdysone, insulin, or an agent that mimics their action, such as the ecdysone agonist, methoxyfenozide. Those cell growing processes resemble nerve cells, and the present study evaluates the ultrastructure of these cultures by transmission electron microscopy. Sf21 cells treated with 20-hydroxyecdysone (with or without veratridine amendment) and subjected to ultrastructural analysis had a similar somatic appearance to control cells, with slight changes in organelles and organization, such as a greater number of cytoplasmic vacuoles and mitochondrial granules. Finger-like projections were observed between control and treated cells. However, no structural markers of synaptic contacts (e.g., vesicles or synaptic thickenings) were observed in controls, 20-hydroxyecdysone, or 20-hydroxyecdysone + veratridine treated cells. It is concluded that additional agents would be required to induce functional synaptogenesis in Sf21 cells.

Pharmaceutical technologies with potential application to insecticide discovery†

Novel neuroactive insecticides are discovered/registered differently, have a lower value in use, and exert their physiological actions in manners distinct from neuroactive pharmaceuticals, but there are clear similarities in their biochemical modes of action. Insecticides are generally discovered using whole pest insect screens, and this eases difficulties in 'translational science' from laboratory to field, as opposed to pharmaceutical translation from biochemical or cell-based targets to animal models to human clinical trials to registered drug. This paper examines recent trends in pharmaceutical science and identifies some technologies which may represent complementary approaches to insecticide discovery screening and mode of action determination beyond the sound processes in common practice today. Examples will be drawn from nanoparticle delivery of neuroactives, unique ligand-polymer conjugates, proposed advances in insect cell culture following from pharmaceutical cell biology, and laboratory or organ-on-a-chip approaches. It is hoped that these concepts will stimulate novel thinking which may enable discovery of efficacious new neuroactive insecticides. © 2020 Society of Chemical Industry.

Efficient neural spike sorting using data subdivision and unification

Neural spike sorting is prerequisite to deciphering useful information from electrophysiological data recorded from the brain, in vitro and/or in vivo. Significant advancements in nanotechnology and nanofabrication has enabled neuroscientists and engineers to capture the electrophysiological activities of the brain at very high resolution, data rate and fidelity. However, the evolution in spike sorting algorithms to deal with the aforementioned technological advancement and capability to quantify higher density data sets is somewhat limited. Both supervised and unsupervised clustering algorithms do perform well when the data to quantify is small, however, their efficiency degrades with the increase in the data size in terms of processing time and quality of spike clusters being formed. This makes neural spike sorting an inefficient process to deal with large and dense electrophysiological data recorded from brain. The presented work aims to address this challenge by providing a novel data pre-processing framework, which can enhance the efficiency of the conventional spike sorting algorithms significantly. The proposed framework is validated by applying on ten widely used algorithms and six large feature sets. Feature sets are calculated by employing PCA and Haar wavelet features on three widely adopted large electrophysiological datasets for consistency during the clustering process. A MATLAB software of the proposed mechanism is also developed and provided to assist the researchers, active in this domain.