Tuning in to the brain’s neural network

The brain: how much don’t we know? Dr Jim Ross, Chief Technology Officer and Co-founder of Axion BioSystems, asks and discusses the answers to this question.

Epilepsy, amyotrophic lateral sclerosis (ALS), Alzheimer’s — we hear these brain disease names all the time, but it feels like we never hear about effective treatments or cures. While medical advances are gradually helping researchers understand the brain and address neurological disease, it is an incredibly complex organ that is difficult to study in a lab setting. When it comes to making better therapies for neurological diseases, medical science often simply does not have a sufficient understanding of their etiology at the cellular and molecular level to effectively mitigate symptoms or halt and reverse damage.

Looking for the cellular changes and molecular abnormalities underlying a disease can often be like looking for a needle in a haystack. The brain is made up of tens of billions of electroactive neurons that pass electrical and chemical signals to one another. Signaling between neurons forms neural circuits and complex networks that together govern the body’s physiology. The cells, circuits, and networks all have distinct roles that contribute to the brain’s overall functionality. While neuroscientists have found creative ways to map and decipher this organ, roadblocks have stifled key advances in understanding the link between the brain’s structure and function – and how these attributes contribute to health and disease.

For example, as many as one in every 100 newborns are diagnosed with paediatric epilepsy.This is a particularly devastating form of the disease that wreaks havoc on patients at the very start of their lives. There are no predictive biomarkers to help doctors determine what treatment will work for a patient.2 Instead, healthcare teams must take a trial-and-error approach in the hopes of finding a treatment to which a patient responds well. However, for about one-third of paediatric epilepsy cases, all treatments fail.2 It takes precious time to sequentially test different drugs, and this can be particularly detrimental to pediatric patients who experience cognitive, behavioural, and emotional changes, and sometimes early death because of their seizures.

A host of different neurological diseases can also strike later in life: for example, ALS affects middle-aged individuals, manifesting in roughly one out of every 50,000 people.ALS cuts people down in their prime, deteriorating motor control and eventually causing death. Despite the dramatic symptoms this disease causes, there is no definitive treatment or even diagnostic criteria for ALS, highlighting how much we must still learn about its origins within the brain.3

There is a sense of urgency in the medical field to better understand and treat these devastating diseases. In the cases of epilepsy and ALS, both affect neuron signaling and electrical activity throughout neural networks. To understand how and why brain activity changes in these patients, scientists must use electrophysiology methods to identify molecular abnormalities in diseased cells, find therapeutic targets, and identify the drugs that will be most effective in counteracting the diseases.

Searching for a window into the brain

Electrophysiology is used to study neural tissue in lab settings under varying conditions. It typically consists of examining one or a few individual cells in a dish in vitro to gain detailed insight into how neurons signal and exhibit electrical changes in response to different stimuli. One of the most well-known electrophysiology methods is called whole-cell patch clamp electrophysiology. The technique is highly complex and requires a degree of delicacy that puts a surgeon’s hand to shame.

To conduct the technique, a researcher must harvest neurons or slices of brain tissue from a live organism. The researcher then inserts a micropipette into each neuron to measure voltage or current. Different stimuli may change the neuron’s voltage or current, but because the pipette has punctured the cell membrane, these changes can only be measured reliably for a matter of minutes before it dies. While this technique has been instrumental in gaining insight into the behavior of ion channels and how single neurons respond to other stimuli, it is not capable of modeling extensive brain activity throughout networks of cells. Furthermore, this technique is incredibly difficult to master and can be inefficient. Scientists typically take a year or more to become sufficiently well-trained on how to prepare, run, and analyse these experiments. Even a highly trained neuroscientist can typically observe at most a handful of neurons per day.

One alternative to help understand brain signaling in action is to study it in a live organism, but then anatomy presents a challenge: the brain is encased in a shield of bone. To study a live brain, scientists must rely on imaging technologies like MRI and CT scans, but these only provide a low-resolution sense of where in the brain activity is occurring. It can be difficult to interpret differences between healthy individuals and patients experiencing malfunction. Due to a lack of detail, this approach can only provide measurements in broad strokes that hint at the brain’s complex and dynamic nature.

A new tool to fill in the gaps 

Challenges precluding a deeper understanding of the brain leave pathologists studying neurological diseases with their hands tied: the methods currently available do not give fast or clear insight into the cellular and molecular mechanisms underlying these diseases. They also do not capture the complex signaling network underlying the system as a whole. Therefore, pathologists’ ability to anticipate which therapies might be most effective is limited. However, recent advances have produced a technology that relies on microelectrode arrays (MEAs) that makes conducting electrophysiology experiments more accessible than ever before. With it, seasoned neuroscientists and novices alike can run long-term experiments and conduct analyses that yield detailed insight into neural networks over time.

The MEA technology, developed by Axion BioSystems, is designed to map the electrical activity of cells in a dish. To run an MEA experiment, scientists culture cells in a multiwell plate that has closely spaced electrodes embedded in the bottom of each well. Axion’s MEA technology maintains delicate surface contact with electrically active cells and detects changes noninvasively so as not to damage the cells. The MEA reader mimics the environment of a cell culture incubator, such that the cellular activity is measured reliably over the lifespan of the culture, from days to months. Axion’s MEA technology complements in vitro electrophysiology approaches that give insight into the behavior of individual cells, enabling researchers to ask additional layers of questions about how those cells interact.

This technique is meant to capture cells in a state that emulates how cells behave in the brain. Neurons and other electrically active cells may be cultured directly in the MEA plate, giving them time to form a network. [Figure 1] Additionally, the multiwell format lends itself especially well to experiments that require multiple replicates or call for multiple variables to be tested. Unlike lower-throughput electrophysiology techniques, a single multiwell MEA plate can simultaneously measure electrical changes induced by multiple genetic, environmental, and pharmacological variables. The technique is also easy to learn: Anyone who has been trained to use cell cultures can conduct an MEA assay.

Thanks to its accessibility, Axion’s MEA technology is already enabling a new wave of research to address some of the most devastating neurological diseases. Promising studies have demonstrated its utility in the development of drugs to treat ALS and personalised therapies for pediatric epilepsy patients. When used in tandem with existing techniques, MEA technology promises to add layers of understanding to give scientists—even those without deep training in neuroscience techniques—the opportunity to study the electrical properties of cells on the bench in real time. Below, we’ll examine how Evangelos Kiskinis, PhD, Assistant Professor of Neurology at Northwestern University Feinberg School of Medicine, used MEA technology to get a deeper look into not one, but two neurological diseases: pediatric epilepsy and ALS. In each instance, the research led to new treatments and hope for patients with these conditions.

Studying paediatric epilepsy with MEA Technology

Epilepsy is a highly patient-specific disease. While scientists traditionally study it in animal models, these models cannot capture patient-specific phenotypes, relevant biomarkers, or potential therapeutic targets. Therefore, Kiskinis’s team used induced pluripotent stem cells (iPSCs) harvested from specific patients. He differentiated the iPSCs into neurons to study each patients’ unique manifestation of the disease. Using MEA technology, Kiskinis’s team was able to study the patients’ cells’ electrical patterns to learn how they would respond to different treatments. His method bypassed the standard trial and error procedure where the patient must take each drug to determine if it will help, relying instead on MEA assays to rapidly indicate the best path forward. Through these studies, Kiskinis hopes to find biomarkers that can be used to match patients to the drugs that will help them most.

The process of finding the right drug to treat an epilepsy patient is especially complicated because the disease has many different subtypes. Kiskinis focused his next study on one subtype, KCNQ2-associated epilepsy. Children with this disease subtype display a characteristic “burst-suppression activity pattern” defined by intermittent periods of highly synchronised firing following by periods of low activity.4 To model KCNQ2-associated epilepsy, Kiskinis’s team grew iPSC-derived neurons taken from patients harboring different mutations in the KCNQ2 gene. Kiskinis compared the cells’ firing activity to the firing pattern seen in brain EEGs of children with this disease. Remarkably, after monitoring the spontaneous activity of KCNQ2-mutant neurons in an MEA plate over several weeks, Kiskinis observed that the cells displayed a remarkably similar burst-suppression firing pattern when compared to an EEG of the patient whom the cells originated from. [Figure 2] Based on these results, Kiskinis’s MEA-based method can be used to create a patient-specific ‘epilepsy-in-a-dish’ model that could become a more personalised, targeted tool to assess therapeutic options for patients.

Uncovering a Potential ALS Biomarker

The Kiskinis lab also used MEA technology to create an ‘ALS-in-a-dish’ model that enabled an existing drug for treating epilepsy, ezogabine, to advance directly into a phase II clinical trial.5 Using their previous strategy, the Kiskinis lab generated neurons from the iPSCs, this time from ALS patients that carried a particular gene mutation: SOD1A4V. They grew the neurons in a multiwell plate, allowing for MEA assay-based observation of several parameters at once. Neurons grown alone were hyperexcitable, as revealed by MEA assays.6 Blocking inhibitory neurons had no effect, indicating that the increased activity was due to motor neuron hyperexcitability. However, when the SOD1 mutation in the neurons was corrected, returning the cells to a wildtype phenotype, their hyperactive electrophysiology reverted to normal.

Notably, classic patch clamp techniques were also used in these studies to identify functional abnormalities in a class of ion channel in the SOD1A4V neurons, likely linked to their hyperexcitability. Finally, Kiskinis’s team ran both MEA and patch clamp assays to show that treating neurons with ezogabine, which restores ion channel activity to normal, reduced hyperexcitability and improved cell survival times in their ALS model. Overall, this research is a powerful illustration of how patch-clamp and MEA technologies can be used in tandem to generate comprehensive, actionable results.

The revelation that ezogabine could reverse the hyperexcitability of SOD1A4V neurons in a dish led Kiskinis and collaborators to test if addressing neuronal hyperexcitability may serve to treat patients, too. After treating ALS patients with different concentrations of ezogabine, the researchers observed a dose-dependent decrease in neuronal excitability. In future studies, Kiskinis and his team must determine if ezogabine truly slows ALS disease progression. Overall, these results offer a promising prospect: that changes in neuronal excitability may serve as a biomarker to help find new ALS drugs.

Conclusion 

The studies conducted in the Kiskinis lab provide just a snapshot of how MEA technology can be used to enable breakthroughs in the study of neurological disease. MEA technology is highly versatile, amenable to studying the behavior of any electroactive cells over time. And because MEA assays do not require significant additional training to use, it opens up the possibility for an additional segment of the neuroscience community to run electrophysiology experiments, in addition to those scientists who are already trained in the classic, technically challenging methods. When MEA assays are used in combination with patch clamp electrophysiology, researchers can gain insight into how individual cells and their communications change as a result of neurological disease of all kinds. As was put to practice in the Kiskinis lab, these tactics can be used to test complex models of disease to uncover biomarkers and shed light on possible treatments that have remained obscure for so long.

About the author

Dr. Jim Ross is the Chief Technology Officer and co-founder of Axion BioSystems, a company that develops instrumentation to support bioelectronic assays in the life sciences. Bioelectronic assays allow scientists to precisely and continuously monitor cultured cells without labels or dyes. 

Figure 1: Depiction of a neuron (left) and a network of neurons (right) growing above an MEA apparatus. Changes in voltage are recorded over time and can be visualised continuously by the green line, while individual action potentials can be tracked, with a white tally mark occurring at each time a signal is picked up by one of 16 electrodes.
Figure 2: Patients carrying a mutation in the KCNQ2 gene display a burst suppression firing pattern, defined by periods of highly synchronised firing followed by stretches of very little activity. The ‘Epilepsy-in-a-dish’ model allowed the Kiskinis lab to show that patients’ burst suppression firing pattern as measured by EEG closely aligned with the behavior of neurons derived from their iPSCs in an MEA assay. (Data provided by the Kiskinis Lab, Northwestern University)

References

  1. KM Aaberg, N Gunnes, IJ Bakken, et al. Incidence and Prevalence of Childhood Epilepsy: A Nationwide Cohort Study. Pediatrics. (2017) 139(5):e20163908. 
  2. As epilepsy drugs fail nearly one-third of patients, scientists seek root causes of seizures. Science. https://www.sciencemag.org/news/2019/12/epilepsy-drugs-fail-nearly-one-third-patients-scientists-seek-root-causes-seizures 
  3. ALS Association FYI: Epidemiology of ALS and Suspected Clusters. https://www.als.org/navigating-als/resources/fyi-epidemiology-als-and-suspected-clusters  
  4. Simkin D et al., Dyshomeostatic modulation of Ca2+-activated K+ channels in a human neuronal model of KCNQ2 encephalopathy. eLife (2021) 10:e64434 
  5. Wainger B et al. Intrinsic Membrane Hyperexcitability of Amyotrophic Lateral Sclerosis Patient-Derived Motor Neurons. Cell Rep (2014) 7(1): 1-11 
  6. Wainger B et al., Effect of Ezogabine on Cortical and Spinal Motor Neuron Excitability in Amyotrophic Lateral Sclerosis. JAMA Neurol. (2021) 78(2):186-196

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