Application of multielectrode array (MEA) chips for the evaluation of mixtures neurotoxicity

Bioelectronic tools for understanding the universal language of electrical signaling across species and kingdoms

Modern bioelectronic tools are rapidly advancing to detect electric potentials within networks of electrogenic cells, such as cardiomyocytes, neurons, and pancreatic beta cells. However, it is becoming evident that electrical signaling is not limited to the animal kingdom but may be a universal form of cell-cell communication. In this review, we discuss the existing evidence of, and tools used to collect, subcellular, single-cell and network-level electrical signals across kingdoms, including bacteria, plants, fungi, and even viruses. We discuss how cellular networks employ altered electrical "circuitry" and intercellular mechanisms across kingdoms, and we assess the functionality and scalability of cutting-edge nanobioelectronics to collect electrical signatures regardless of cell size, shape, or function. Researchers today aim to design micro- and nano-topographic structures which harness mechanosensitive membrane and cytoskeletal pathways that enable tight electrical coupling to subcellular compartments within high-throughput recording systems. Finally, we identify gaps in current knowledge of inter-species and inter-kingdom electrical signaling and propose critical milestones needed to create a central theory of electrical signaling across kingdoms. Our discussion demonstrates the need for high resolution, high throughput tools which can probe multiple, diverse cell types at once in their native or experimentally-modeled environments. These advancements will not only reveal the underlying biophysical laws governing the universal language of electrical communication, but can enable bidirectional electrical communication and manipulation of biological systems.

A Machine-Learning-Driven Pathophysiology-Based New Approach Method for the Dose-Dependent Assessment of Hazardous Chemical Mixtures and Experimental Validations

Environmental chemicals, such as PFAS, exist as mixtures and are frequently encountered at varying concentrations, which can lead to serious health effects, such as cancer. Therefore, understanding the dose-dependent toxicity of chemical mixtures is essential for health risk assessment. However, comprehensive methods to assess toxicity and identify the mechanisms of these harmful mixtures are currently absent. In this study, the dose-dependent toxicity assessments of chemical mixtures are performed in three methodologically distinct phases. In the first phase, we evaluated our machine-learning method (AI-HNN) and pathophysiology method (CPTM) for predicting toxicity. In the second phase, we integrated AI-HNN and CPTM to establish a comprehensive new approach method (NAM) framework called AI-CPTM that is targeted at refining prediction accuracy and providing a comprehensive understanding of toxicity mechanisms. The third phase involved experimental validations of the AI-CPTM predictions. Initially, we developed binary, multiclass classification, and regression models to predict binary, categorical toxicity, and toxic potencies using nearly a thousand experimental mixtures. This empirical dataset was expanded with assumption-based virtual mixtures, compensating for the lack of experimental data and broadening the scope of the dataset. For comparison, we also developed machine-learning models based on RF, Bagging, AdaBoost, SVR, GB, KR, DT, KN, and Consensus methods. The AI-HNN achieved overall accuracies of over 80%, with the AUC exceeding 90%. In the final phase, we demonstrated the superior performance and predictive capability of AI-CPTM, including for PFAS mixtures and their interaction effects, through rigorous literature and statistical validations, along with experimental dose-response zebrafish-embryo toxicity assays. Overall, the AI-CPTM approach significantly improves upon the limitations of standalone AI models, showing extensive enhancements in identifying toxic chemicals and mixtures and their mechanisms. This study is the first to develop a hybrid NAM that integrates AI with a pathophysiology method to comprehensively predict chemical-mixture toxicity, carcinogenicity, and mechanisms.

Development of a new hazard scoring system in primary neuronal cell cultures for drug-induced acute neuronal toxicity identification in early drug discovery

We investigated drug-induced acute neuronal electrophysiological changes using Micro-Electrode arrays (MEA) to rat primary neuronal cell cultures. Data based on 6-key MEA parameters were analyzed for plate-to-plate vehicle variability, effects of positive and negative controls, as well as data from over 100 reference drugs, mostly known to have pharmacological phenotypic and clinical outcomes. A Least Absolute Shrinkage and Selection Operator (LASSO) regression, coupled with expert evaluation helped to identify the 6-key parameters from many other MEA parameters to evaluate the drug-induced acute neuronal changes. Calculating the statistical tolerance intervals for negative-positive control effects on those 4-key parameters helped us to develop a new weighted hazard scoring system on drug-induced potential central nervous system (CNS) adverse effects (AEs). The weighted total score, integrating the effects of a drug candidate on the identified six-pivotal parameters, simply determines if the testing compound/concentration induces potential CNS AEs. Hereto, it uses four different categories of hazard scores: non-neuroactive, neuroactive, hazard, or high hazard categories. This new scoring system was successfully applied to differentiate the new compounds with or without CNS AEs, and the results were correlated with the outcome of in vivo studies in mice for one internal program. Furthermore, the Random Forest classification method was used to obtain the probability that the effect of a compound is either inhibitory or excitatory. In conclusion, this new neuronal scoring system on the cell assay is actively applied in the early de-risking of drug development and reduces the use of animals and associated costs.

Spatiotemporal analysis of 3D human iPSC-derived neural networks using a 3D multi-electrode array

While there is a growing appreciation of three-dimensional (3D) neural tissues (i.e., hydrogel-based, organoids, and spheroids), shown to improve cellular health and network activity to mirror brain-like activity in vivo, functional assessment using current electrophysiology techniques (e.g., planar multi-electrode arrays or patch clamp) has been technically challenging and limited to surface measurements at the bottom or top of the 3D tissue. As next-generation MEAs, specifically 3D MEAs, are being developed to increase the spatial precision across all three dimensions (X, Y, Z), development of improved computational analytical tools to discern region-specific changes within the Z dimension of the 3D tissue is needed. In the present study, we introduce a novel computational analytical pipeline to analyze 3D neural network activity recorded from a "bottom-up" 3D MEA integrated with a 3D hydrogel-based tissue containing human iPSC-derived neurons and primary astrocytes. Over a period of ~6.5 weeks, we describe the development and maturation of 3D neural activity (i.e., features of spiking and bursting activity) within cross sections of the 3D tissue, based on the vertical position of the electrode on the 3D MEA probe, in addition to network activity (identified using synchrony analysis) within and between cross sections. Then, using the sequential addition of postsynaptic receptor antagonists, bicuculline (BIC), 2-amino-5-phosphonovaleric acid (AP-5), and 6-cyano-5-nitroquinoxaline-2,3-dione (CNQX), we demonstrate that networks within and between cross sections of the 3D hydrogel-based tissue show a preference for GABA and/or glutamate synaptic transmission, suggesting differences in the network composition throughout the neural tissue. The ability to monitor the functional dynamics of the entire 3D reconstructed neural tissue is a critical bottleneck; here we demonstrate a computational pipeline that can be implemented in studies to better interpret network activity within an engineered 3D neural tissue and have a better understanding of the modeled organ tissue.

Integration of toxicodynamic and toxicokinetic new approach methods into a weight-of-evidence analysis for pesticide developmental neurotoxicity assessment: A case-study with DL- and L-glufosinate

DL-glufosinate ammonium (DL-GLF) is a registered herbicide for which a guideline Developmental Neurotoxicity (DNT) study has been conducted. Offspring effects included altered brain morphometrics, decreased body weight, and increased motor activity. Guideline DNT studies are not available for its enriched isomers L-GLF acid and L-GLF ammonium; conducting one would be time consuming, resource-intensive, and possibly redundant given the existing DL-GLF DNT. To support deciding whether to request a guideline DNT study for the L-GLF isomers, DL-GLF and the L-GLF isomers were screened using in vitro assays for network formation and neurite outgrowth. DL-GLF and L-GLF isomers were without effects in both assays. DL-GLF and L-GLF (1-100 μM) isomers increased mean firing rate of mature networks to 120-140% of baseline. In vitro toxicokinetic assessments were used to derive administered equivalent doses (AEDs) for the in vitro testing concentrations. The AED for L-GLF was ∼3X higher than the NOAEL from the DL-GLF DNT indicating that the available guideline study would be protective of potential DNT due to L-GLF exposure. Based in part on the results of these in vitro studies, EPA is not requiring L-GLF isomer guideline DNT studies, thereby providing a case study for a useful application of DNT screening assays.

Use of ammonium salts or binary mixtures derived from amino acids, glycine betaine, choline and indole-3-butyric acid as plant regulators

A simple, efficient, and environmentally friendly synthesis method for bioproducts based on indole-3-butyric acid and amino acids, glycine betaine or choline has been developed. Spectral analysis and molecular calculations were used to determine whether the products were ammonium salts or binary mixtures. Moreover, it was observed that the ammonium salts degraded more rapidly than the binary mixtures when exposed to light. The structures of the products significantly impacted their thermal stability and phase transitions. Biological studies clearly showed that the synthesized products were more effective than a reference commercial preparation as a rooting agent and have significant potential as new biologically active agents with low environmental impact.

Innovations in 3-Dimensional Tissue Models of Human Brain Physiology and Diseases

3-dimensional (3D) laboratory tissue cultures have emerged as an alternative to traditional 2-dimensional (2D) culture systems that do not recapitulate native cell behavior. The discrepancy between in vivo and in vitro tissue-cell-molecular responses impedes understanding of human physiology in general and creates roadblocks for the discovery of therapeutic solutions. Two parallel approaches have emerged for the design of 3D culture systems. The first is biomedical engineering methodology, including bioengineered materials, bioprinting, microfluidics and bioreactors, used alone or in combination, to mimic the microenvironments of native tissues. The second approach is organoid technology, in which stem cells are exposed to chemical and/or biological cues to activate differentiation programs that are reminiscent of human (prenatal) development. This review article describes recent technological advances in engineering 3D cultures that more closely resemble the human brain. The contributions of in vitro 3D tissue culture systems to new insights in neurophysiology, neurological diseases and regenerative medicine are highlighted. Perspectives on designing improved tissue models of the human brain are offered, focusing on an integrative approach merging biomedical engineering tools with organoid biology.

Optimized nonionic emulsifier for the efficient delivery of astaxanthin nanodispersions to retina: in vivo and ex vivo evaluations

Astaxanthin (AST) is a naturally occurring carotenoid with potent anti-oxidative and anti-inflammatory potency against chronic diseases. In this study, we suspended AST in different nonionic emulsifiers to produce nanodispersions. The basic physicochemical properties of the produced AST nanodispersions were verified to select the optimized nonionic emulsifier. Among the tested emulsifiers, Polysorbate 20 produced the AST nanoemulsions with smaller particle diameters, narrower size distributions, and higher AST contents among these emulsifiers. The N-methyl-N-nitrosourea (MNU) administered mouse is a chemically induced retinal degeneration (RD) model with rapid progress rate. AST suspended in Polysorbate 20 was demonstrated to ameliorate the dramatic consequences of MNU on retina architectures and function in several different tests encompassing from electrophysiology to histology and molecular tests. Furthermore, the multi-electrodes array (MEA) was used to detect the firing activities of retinal ganglion cells within the inner retinal circuits. We found that AST nanodispersions could restrain the spontaneous firing response, enhance the light induced firing response, and preserve the basic configurations of visual signal pathway in degenerative retinas. The MEA assay provided an appropriate example to evaluate the potency of pharmacological compounds on retinal plasticity. In summary, emulsifier type affects the basic physicochemical characteristic of AST nanodispersions. Polysorbate 20 acts as an optimized nonionic emulsifier for the efficient delivery of AST nanodispersions to retina. AST nanodispersions can alleviate the photoreceptor loss and rectify the abnormities in visual signal transmission.

Concentration-response evaluation of ToxCast compounds for multivariate activity patterns of neural network function

The US Environmental Protection Agency's ToxCast program has generated toxicity data for thousands of chemicals but does not adequately assess potential neurotoxicity. Networks of neurons grown on microelectrode arrays (MEAs) offer an efficient approach to screen compounds for neuroactivity and distinguish between compound effects on firing, bursting, and connectivity patterns. Previously, single concentrations of the ToxCast Phase II library were screened for effects on mean firing rate (MFR) in rat primary cortical networks. Here, we expand this approach by retesting 384 of those compounds (including 222 active in the previous screen) in concentration-response across 43 network activity parameters to evaluate neural network function. Using hierarchical clustering and machine learning methods on the full suite of chemical-parameter response data, we identified 15 network activity parameters crucial in characterizing activity of 237 compounds that were response actives ("hits"). Recognized neurotoxic compounds in this network function assay were often more potent compared to other ToxCast assays. Of these chemical-parameter responses, we identified three k-means clusters of chemical-parameter activity (i.e., multivariate MEA response patterns). Next, we evaluated the MEA clusters for enrichment of chemical features using a subset of ToxPrint chemotypes, revealing chemical structural features that distinguished the MEA clusters. Finally, we assessed distribution of neurotoxicants with known pharmacology within the clusters and found that compounds segregated differentially. Collectively, these results demonstrate that multivariate MEA activity patterns can efficiently screen for diverse chemical activities relevant to neurotoxicity, and that response patterns may have predictive value related to chemical structural features.

Functional characterization of human pluripotent stem cell-derived cortical networks differentiated on laminin-521 substrate: comparison to rat cortical cultures

Human pluripotent stem cell (hPSC)-derived neurons provide exciting opportunities for in vitro modeling of neurological diseases and for advancing drug development and neurotoxicological studies. However, generating electrophysiologically mature neuronal networks from hPSCs has been challenging. Here, we report the differentiation of functionally active hPSC-derived cortical networks on defined laminin-521 substrate. We apply microelectrode array (MEA) measurements to assess network events and compare the activity development of hPSC-derived networks to that of widely used rat embryonic cortical cultures. In both of these networks, activity developed through a similar sequence of stages and time frames; however, the hPSC-derived networks showed unique patterns of bursting activity. The hPSC-derived networks developed synchronous activity, which involved glutamatergic and GABAergic inputs, recapitulating the classical cortical activity also observed in rodent counterparts. Principal component analysis (PCA) based on spike rates, network synchronization and burst features revealed the segregation of hPSC-derived and rat network recordings into different clusters, reflecting the species-specific and maturation state differences between the two networks. Overall, hPSC-derived neural cultures produced with a defined protocol generate cortical type network activity, which validates their applicability as a human-specific model for pharmacological studies and modeling network dysfunctions.

Simultaneous electrophysiological and morphological assessment of functional damage to neural networks in vitro after 30-300 g impacts

An enigma of mild traumatic brain injury are observations of substantial behavior and performance deficits in the absence of bleeding or other observable structural damage. Altered behavior and performance reflect changes in action potential (AP) patterns within neuronal networks, which could result from subtle subcellular responses that affect synaptic efficacy and AP production. The aim of this study was to investigate and quantify network activity changes after simulated concussions in vitro and therewith develop a platform for simultaneous and direct observations of morphological and electrophysiological changes in neural networks. We used spontaneously active networks grown on microelectrode arrays (MEAs) to allow long-term multisite monitoring with simultaneous optical observations before and after impacts delivered by a ballistic pendulum (30 to 300 g accelerations). The monitoring of AP waveshape templates for long periods before and after impact provided an internal control for cell death or loss of cell-electrode coupling in the observed set of neurons. Network activity patterns were linked in real-time to high power phase contrast microscopy. There was no overt loss of glial or neuronal adhesion, even at high-g impacts. All recording experiments showed repeatable spike production responses: a loss of activity with recovery to near reference in 1 hr, followed by a slow activity decay to a stable, level plateau approximately 30–40% below reference. The initial recovery occurred in two steps: a rapid return of activity to an average 24% below reference, forming a level plateau lasting from 5 to 20 min, followed by a climb to within 10% of reference where a second plateau was established for 1 to 2 hrs. Cross correlation profiles revealed changes in firing hierarchy as well as in Phase 1 in spontaneous network oscillations that were reduced by as much as 20% 6–8 min post impact with only a partial recovery at 30 min. We also observed that normally stable nuclei developed irregular rotational motion after impact in 27 out of 30 networks. The evolution of network activity deficits and recovery can be linked with microscopically observable changes in the very cells that are generating the activity. The repeatable electrophysiological impact response profiles and oscillation changes can provide a quantitative basis for systematic evaluations of pharmacological intervention strategies. Future expansion to include fluorescent microscopy should allow detailed investigations of damage mechanisms on the subcellular level.

Neurotoxicity of pesticides

Pesticides are unique environmental contaminants that are specifically introduced into the environment to control pests, often by killing them. Although pesticide application serves many important purposes, including protection against crop loss and against vector-borne diseases, there are significant concerns over the potential toxic effects of pesticides to non-target organisms, including humans. In many cases, the molecular target of a pesticide is shared by non-target species, leading to the potential for untoward effects. Here, we review the history of pesticide usage and the neurotoxicity of selected classes of pesticides, including insecticides, herbicides, and fungicides, to humans and experimental animals. Specific emphasis is given to linkages between exposure to pesticides and risk of neurological disease and dysfunction in humans coupled with mechanistic findings in humans and animal models. Finally, we discuss emerging techniques and strategies to improve translation from animal models to humans.

Application of Microelectrode Array Approaches to Neurotoxicity Testing and Screening

Neurotoxicity can be defined by the ability of a drug or chemical to alter the physiology, biochemistry, or structure of the nervous system in a manner that may negatively impact the health or function of the individual. Electrophysiological approaches have been utilized to study the mechanisms underlying neurotoxic actions of drugs and chemicals for over 50 years, and in more recent decades, high-throughput patch-clamp approaches have been utilized by the pharmaceutical industry for drug development. The use of microelectrode array recordings to study neural network electrophysiology is a relatively newer approach, with commercially available systems becoming available only in the early 2000s. However, MEAs have been rapidly adopted as a useful approach for neurotoxicity testing. In this chapter, I will review the use of MEA approaches as they have been applied to the field of neurotoxicity testing, especially as they have been applied to the need to screen large numbers of chemicals for neurotoxicity and developmental neurotoxicity. In addition, I will also identify challenges for the field that when addressed will improve the utility of MEA approaches for toxicity testing.

Effects of an environmentally-relevant mixture of pyrethroid insecticides on spontaneous activity in primary cortical networks on microelectrode arrays

Pyrethroid insecticides exert their insecticidal and toxicological effects primarily by disrupting voltage-gated sodium channel (VGSC) function, resulting in altered neuronal excitability. Numerous studies of individual pyrethroids have characterized effects on mammalian VGSC function and neuronal excitability, yet studies examining effects of complex pyrethroid mixtures in mammalian neurons, especially in environmentally relevant mixture ratios, are limited. In the present study, concentration-response functions were characterized for five pyrethroids (permethrin, deltamethrin, cypermethrin, β-cyfluthrin and esfenvalerate) in an in vitro preparation containing cortical neurons and glia. As a metric of neuronal network activity, spontaneous mean network firing rates (MFR) were measured using microelectorde arrays (MEAs). In addition, the effect of a complex and exposure relevant mixture of the five pyrethroids (containing 52% permethrin, 28.8% cypermethrin, 12.9% β-cyfluthrin, 3.4% deltamethrin and 2.7% esfenvalerate) was also measured. Data were modeled to determine whether effects of the pyrethroid mixture were predicted by dose-addition. At concentrations up to 10μM, all compounds except permethrin reduced MFR. Deltamethrin and β-cyfluthrin were the most potent and reduced MFR by as much as 60 and 50%, respectively, while cypermethrin and esfenvalerate were of approximately equal potency and reduced MFR by only ∼20% at the highest concentration. Permethrin caused small (∼24% maximum), concentration-dependent increases in MFR. Effects of the environmentally relevant mixture did not depart from the prediction of dose-addition. These data demonstrate that an environmentally relevant mixture caused dose-additive effects on spontaneous neuronal network activity in vitro, and is consistent with other in vitro and in vivo assessments of pyrethroid mixtures.

The virtual cell based assay: Current status and future perspectives

In order to replace the use of animals in toxicity testing, there is a need to predict in vivo toxic doses from concentrations that cause toxicological effects in relevant in vitro systems. The Virtual Cell Based Assay (VCBA) estimates time-dependent concentration of a test chemical in the cell and cell culture for a given in vitro system. The concentrations in the different compartments of the cell and test system are derived from ordinary differential equations, physicochemical parameters of the test chemical and properties of the cell line. The VCBA has been developed for a range of cell lines including BALB/c 3T3 cells, HepG2, HepaRG, lung A459 cells, and cardiomyocytes. The model can be used to design and refine in vitro experiments and extrapolate in vitro effective concentrations to in vivo doses that can be applied in risk assessment. In this paper, we first discuss potential applications of the VCBA: i) design of in vitro High Throughput Screening (HTS) experiments; ii) hazard identification (based on acute systemic toxicity); and iii) risk assessment. Further extension of the VCBA is discussed in the second part, exploring potential application to i) manufactured nanomaterials, ii) additional cell lines and endpoints, and considering iii) other opportunities.

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VCBA as an alternative approach can be applied in the domain of nanotoxicology.

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VCBA can support better testing strategies in acute toxicity.

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Refinement of the VCBA taking into account biological oscillators could improve toxicity prediction.

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Extensions of the VCBA can capture effects related to additional subcellular compartments.

Pharmacological response sensitization in nerve cell networks exposed to the antibiotic gentamicin

Gentamicin is an aminoglycoside antibiotic that is used in clinical, organismic, and agricultural applications to combat gram-negative, aerobic bacteria. The clinical use of gentamicin is widely linked to various toxicities, but there is a void in our knowledge about the neuromodulatory or neurotoxicity effects of gentamicin. This investigation explored the electrophysiologic effects of gentamicin on GABAergic pharmacological profiles in spontaneously active neuronal networks in vitro derived from auditory cortices of E16 mouse embryos and grown on microelectrode arrays. Using the GABA_A agonist muscimol as the test substance, responses from networks to dose titrations of muscimol were compared in the presence and absence of 100µM gentamicin (the recommended concentration for cell culture conditions). Spike-rate based EC₅₀ values were generated using sigmoidal fit concentration response curves (CRCs). Exposure to 100µM gentamicin exhibited a muscimol EC₅₀±S.E.M. of 80±6nM (n=10). The EC₅₀ value obtained in the absence of gentamicin was 124±11nM (n=10). The 35% increase in potency suggests network sensitization to muscimol in the presence of gentamicin. Action potential (AP) waveform analyses of neurons exposed to gentamicin demonstrated a concentration-dependent decrease in AP amplitudes (extracellular recordings), possibly reflecting gentamicin effects on voltage-gated ion channels. These in vitro results reveal alteration of pharmacological responses by antibiotics that could have significant influence on the behavior and performance of animals.

In vitro evaluation of pyrethroid-mediated changes on neuronal burst parameters using microelectrode arrays

Effects of pyrethroids (beta-cyfluthrin, bifenthrin, cypermethrin, deltamethrin, lambda-cyhalothrin, and permethrin) on the burst parameters (mean burst rate [MBR], percent spikes in burst [PSB], mean burst duration [MBD], mean spikes in burst [MSB], mean interspike interval in burst [MISIB], and mean interburst interval [MIBI]) have been investigated using the microelectrode array technique. Rat cortical neuronal networks (between 24 and 35 DIV) were exposed to the five accumulative concentrations of pyrethroids (0.01μM, 0.1μM, 1μM, 10μM, and 100μM) after initially recording the baseline activity. When compared to the baseline, the burst parameter that had undergone the most change (either increase/decrease) at the initial concentrations was MBR, followed by MIBI and PSB. The other burst parameters (MSB, MBD, and MISIB) did not undergo much change (either increase/decrease) by the pyrethroids at the initial concentrations when compared to the baseline. The MBR of all pyrethroids rose at initial concentrations followed by decrease at higher concentrations. A drop in the MIBI accompanied the rise in the MBR. The rank orders of relative potency of pyrethroids on the IC₅₀ of different burst parameters clearly distinguish type-1 pyrethroids (bifenthrin, permethrin) from the type-2 pyrethroids (beta-cyfluthrin, cypermethrin, deltamethrin, lambda-cyhalothrin), with type-2 being more potent. The rank order of relative potency of pyrethroids based on the IC₅₀ of MBR was beta-cyfluthrin>lambda-cyhalothrin>deltamethrin>cypermethrin>bifenthrin>permethrin.

How Microelectrode Array-Based Chick Forebrain Neuron Biosensors Respond to Glutamate NMDA Receptor Antagonist AP5 and GABAA Receptor Antagonist Musimol

We have established a long-term, stable primary chick forebrain neuron (FBN) culture on a microelectrode array platform as a biosensor system for neurotoxicant screening and for neuroelectrophysiological studies for multiple purposes. This paper reports some of our results, which characterize the biosensor pharmacologically. Dose-response experiments were conducted using NMDA receptor antagonist AP5 and GABA_A receptor agonist musimol (MUS). The chick FBN biosensor (C-FBN-biosensor) responds to the two agents in a pattern similar to that of rodent counterparts; the estimated EC₅₀s (the effective concentration that causes 50% inhibition of the maximal effect) are 2.3 μM and 0.25 μM, respectively. Intercultural and intracultural reproducibility and long-term reusability of the C-FBN-biosensor are addressed and discussed. A phenomenon of sensitization of the biosensor that accompanies intracultural reproducibility in paired dose-response experiments for the same agent (AP5 or MUS) is reported. The potential application of the C-FBN-biosensor as an alternative to rodent biosensors in shared sensing domains (NMDA receptor and GABA_A receptor) is suggested.

Microelectrode array (MEA) platform as a sensitive tool to detect and evaluate Ostreopsis cf. ovata toxicity

In the last decade, the occurrence of harmful dinoflagellate blooms of the genus Ostreopsis has increased both in frequency and in geographic distribution with adverse impacts on public health and the economy. Ostreopsis species are producers of palytoxin-like toxins (putative palytoxin and ovatoxins) which are among the most potent natural non-protein compounds known to date, exhibiting extreme toxicity in mammals, including humans. Most existing toxicological data are derived from in vivo mouse assay and are related to acute effects of pure palytoxin, without considering that the toxicity mechanism of dinoflagellates can be dependent on the varying composition of complex biotoxins mixture and on the presence of cellular components. In this study, in vitro neuronal networks coupled to microelectrode array (MEA)-based system are proposed, for the first time, as sensitive biosensors for the evaluation of marine alga toxicity on mammalian cells. Toxic effect was investigated by testing three different treatments of laboratory cultured Ostreopsis cf. ovata cells: filtered and re-suspended algal cells; filtered, re-suspended and sonicated algal cells; conditioned growth medium devoid of algal cells. The great sensitivity of this system revealed the mixture of PTLX-complex analogues naturally released in the growth medium and the different potency of the three treatments to inhibit the neuronal network spontaneous electrical activity. Moreover, by means of the multiparametric analysis of neuronal network activity, the approach revealed a different toxicity mechanism of the cellular component compared to the algal conditioned growth medium, highlighting the potential active role of the first treatment.

A multi-laboratory evaluation of microelectrode array-based measurements of neural network activity for acute neurotoxicity testing

There is a need for methods to screen and prioritize chemicals for potential hazard, including neurotoxicity. Microelectrode array (MEA) systems enable simultaneous extracellular recordings from multiple sites in neural networks in real time and thereby provide a robust measure of network activity. In this study, spontaneous activity measurements from primary neuronal cultures treated with three neurotoxic or three non-neurotoxic compounds was evaluated across four different laboratories. All four individual laboratories correctly identifed the neurotoxic compounds chlorpyrifos oxon (an organophosphate insecticide), deltamethrin (a pyrethroid insecticide) and domoic acid (an excitotoxicant). By contrast, the other three compounds (glyphosate, dimethyl phthalate and acetaminophen) considered to be non-neurotoxic ("negative controls"), produced only sporadic changes of the measured parameters. The results were consistent across the different laboratories, as all three neurotoxic compounds caused concentration-dependent inhibition of mean firing rate (MFR). Further, MFR appeared to be the most sensitive parameter for effects of neurotoxic compounds, as changes in electrical activity measured by mean frequency intra burst (MFIB), and mean burst duration (MBD) did not result in concentration-response relationships for some of the positive compounds, or required higher concentrations for an effect to be observed. However, greater numbers of compounds need to be tested to confirm this. The results obtained indicate that measurement of spontaneous electrical activity using MEAs provides a robust assessment of compound effects on neural network function.

Establishment of a Human Neuronal Network Assessment System by Using a Human Neuron/Astrocyte Co-Culture Derived from Fetal Neural Stem/Progenitor Cells

Using human cell models mimicking the central nervous system (CNS) provides a better understanding of the human CNS, and it is a key strategy to improve success rates in CNS drug development. In the CNS, neurons function as networks in which astrocytes play important roles. Thus, an assessment system of neuronal network functions in a co-culture of human neurons and astrocytes has potential to accelerate CNS drug development. We previously demonstrated that human hippocampus-derived neural stem/progenitor cells (HIP-009 cells) were a novel tool to obtain human neurons and astrocytes in the same culture. In this study, we applied HIP-009 cells to a multielectrode array (MEA) system to detect neuronal signals as neuronal network functions. We observed spontaneous firings of HIP-009 neurons, and validated functional formation of neuronal networks pharmacologically. By using this assay system, we investigated effects of several reference compounds, including agonists and antagonists of glutamate and γ-aminobutyric acid receptors, and sodium, potassium, and calcium channels, on neuronal network functions using firing and burst numbers, and synchrony as readouts. These results indicate that the HIP-009/MEA assay system is applicable to the pharmacological assessment of drug candidates affecting synaptic functions for CNS drug development.

Multi-well microelectrode array recordings detect neuroactivity of ToxCast compounds

Spontaneous activity in neuronal cultures on microelectrode arrays (MEAs) is sensitive to effects of drugs, chemicals, and particles. Multi-well MEA (mwMEA) systems have increased throughput of MEAs, enabling their use for chemical screening. The present experiments examined a subset of EPA's ToxCast compounds for effects on spontaneous neuronal activity in primary cortical cultures using 48-well MEA plates. A first cohort of 68 compounds was selected from the ToxCast Phase I and II libraries; 37 were positive in one or more of 20 individual ToxCast Novascreen assays related to ion channels (NVS_IC), with the remainder selected based on known neuroactivity. A second cohort of 25 compounds was then tested with 20 originating from the ToxCast Phase I and II libraries (not hits in NVS_IC assays) and 5 known negatives from commercial vendors. Baseline activity (1h) was recorded prior to exposing the networks to compounds for 1h, and the weighted mean firing rate (wMFR) was determined in the absence and presence of each compound. Compounds that altered activity by greater than the weighted change of DMSO-treated wells plus 2SD were considered "hits". Of the first set of 68 compounds, 54 altered wMFR by more than the threshold, while in the second set, 13/25 compounds were hits. MEAs detected 30 of 37 (81.1%) compounds that were hits in NVS_IC assays, as well as detected known neurotoxicants that were negative in NVS_IC assays, primarily pyrethroids and GABAA receptor antagonists. Conversely, wMFR of cortical neuronal networks on MEAs was insensitive to nicotinic compounds, as only one neonicotinoid was detected by MEAs; this accounts for the bulk of non-concordant compounds between MEA and NVS_IC assays. These data demonstrate that mwMEAs can be used to screen chemicals efficiently for potential neurotoxicity, and that the results are concordant with predictions from ToxCast NVS_IC assays for interactions with ion channels.

In-vitro exposure of neuronal networks to the GSM-1800 signal

The central nervous system is the most likely target of mobile telephony radiofrequency (RF) field exposure in terms of biological effects. Several electroencephalography (EEG) studies have reported variations in the alpha-band power spectrum during and/or after RF exposure, in resting EEG and during sleep. In this context, the observation of the spontaneous electrical activity of neuronal networks under RF exposure can be an efficient tool to detect the occurrence of low-level RF effects on the nervous system. Our research group has developed a dedicated experimental setup in the GHz range for the simultaneous exposure of neuronal networks and monitoring of electrical activity. A transverse electromagnetic (TEM) cell was used to expose the neuronal networks to GSM-1800 signals at a SAR level of 3.2 W/kg. Recording of the neuronal electrical activity and detection of the extracellular spikes and bursts under exposure were performed using microelectrode arrays (MEAs). This work provides the proof of feasibility and preliminary results of the integrated investigation regarding exposure setup, culture of the neuronal network, recording of the electrical activity, and analysis of the signals obtained under RF exposure. In this pilot study on 16 cultures, there was a 30% reversible decrease in firing rate (FR) and bursting rate (BR) during a 3 min exposure to RF. Additional experiments are needed to further characterize this effect.